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[GH-ISSUE #832] Ollama does not make use of GPU (T4 on Google Colab) #26158

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opened 2026-04-22 02:12:48 -05:00 by GiteaMirror · 18 comments
GiteaMirror commented 2026-04-22 02:12:48 -05:00
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Originally created by @tranhoangnguyen03 on GitHub (Oct 18, 2023).
Original GitHub issue: https://github.com/ollama/ollama/issues/832

I was experimenting with serving an Ollama server over ngrok on Google Colab:

%%bash
sudo curl -L https://ollama.ai/download/ollama-linux-amd64 -o /usr/bin/ollama  
sudo chmod +x /usr/bin/ollama

### ngrok codes to expose port 11434 to public URL

ollama serve mistral-openorca

I was able to CURL the server, but I notice that the server does not make use of the notebook GPU.

I've also tried installing llama.cpp with CUDA but the GPU remains unused:

%%bash
# Install Server with OpenAI Compatible API - with CUDA GPU support
CMAKE_ARGS="-DLLAMA_CUBLAS=on" FORCE_CMAKE=1 pip -q install llama-cpp-python[server]
Originally created by @tranhoangnguyen03 on GitHub (Oct 18, 2023). Original GitHub issue: https://github.com/ollama/ollama/issues/832 I was experimenting with serving an Ollama server over ngrok on Google Colab: ``` %%bash sudo curl -L https://ollama.ai/download/ollama-linux-amd64 -o /usr/bin/ollama sudo chmod +x /usr/bin/ollama ### ngrok codes to expose port 11434 to public URL ollama serve mistral-openorca ``` I was able to CURL the server, but I notice that the server does not make use of the notebook GPU. I've also tried installing llama.cpp with CUDA but the GPU remains unused: ``` %%bash # Install Server with OpenAI Compatible API - with CUDA GPU support CMAKE_ARGS="-DLLAMA_CUBLAS=on" FORCE_CMAKE=1 pip -q install llama-cpp-python[server] ```
GiteaMirror added the question label 2026-04-22 02:12:48 -05:00
GiteaMirror commented 2026-04-22 02:12:50 -05:00
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@mxyng commented on GitHub (Oct 18, 2023):

Can you attach the output logs from ollama serve? It should mention if it detected GPU or not. It will output something like this if there's a problem with GPU support:

2023/10/18 22:30:43 routes.go:634: Warning: GPU support may not enabled, check you have installed install GPU drivers: nvidia-smi command failed

Make sure you select a GPU instance type when using a hosted runtime.

image
<!-- gh-comment-id:1769503141 --> @mxyng commented on GitHub (Oct 18, 2023): Can you attach the output logs from `ollama serve`? It should mention if it detected GPU or not. It will output something like this if there's a problem with GPU support: ``` 2023/10/18 22:30:43 routes.go:634: Warning: GPU support may not enabled, check you have installed install GPU drivers: nvidia-smi command failed ``` Make sure you select a GPU instance type when using a hosted runtime. <img width="561" alt="image" src="https://github.com/jmorganca/ollama/assets/2372640/cab9e3eb-54ec-4d47-b164-38d517c632ef">
GiteaMirror commented 2026-04-22 02:12:50 -05:00
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@tranhoangnguyen03 commented on GitHub (Oct 19, 2023):

image

<!-- gh-comment-id:1769804857 --> @tranhoangnguyen03 commented on GitHub (Oct 19, 2023): ![image](https://github.com/jmorganca/ollama/assets/31383641/ec0999f6-97c2-4b55-a342-4b8ba1d70e84)
GiteaMirror commented 2026-04-22 02:12:51 -05:00
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@tranhoangnguyen03 commented on GitHub (Oct 19, 2023):

Below is the full reading after I ran ollama run mistral. It looks like an issue with the default Ollama CUDA driver

2023/10/19 02:47:55 images.go:995: total blobs: 0
2023/10/19 02:47:55 images.go:1002: total unused blobs removed: 0
2023/10/19 02:47:55 routes.go:614: Listening on 127.0.0.1:11434
2023/10/19 02:48:02 images.go:995: total blobs: 0
2023/10/19 02:48:02 images.go:1002: total unused blobs removed: 0
2023/10/19 02:48:02 routes.go:614: Listening on 127.0.0.1:11434
[GIN] 2023/10/19 - 02:48:23 | 200 |    1.818527ms |       127.0.0.1 | HEAD     "/"
[GIN] 2023/10/19 - 02:48:23 | 200 |     276.108µs |       127.0.0.1 | GET      "/api/tags"
2023/10/19 02:48:25 download.go:126: downloading 6ae280299950 in 64 64 MB part(s)
2023/10/19 02:48:47 download.go:126: downloading fede2d8d6c1f in 1 29 B part(s)
2023/10/19 02:48:50 download.go:126: downloading b96850d2e482 in 1 307 B part(s)
[GIN] 2023/10/19 - 02:49:08 | 200 |  45.31729643s |       127.0.0.1 | POST     "/api/pull"
2023/10/19 02:49:10 llama.go:252: 15101 MiB VRAM available, loading up to 113 GPU layers
2023/10/19 02:49:10 llama.go:356: starting llama runner
2023/10/19 02:49:10 llama.go:408: waiting for llama runner to start responding

CUDA error 35 at /go/src/github.com/jmorganca/ollama/llm/llama.cpp/gguf/ggml-cuda.cu:5522: CUDA driver version is insufficient for CUDA runtime version
current device: -502659984
2023/10/19 02:49:10 llama.go:373: error starting llama runner: llama runner process has terminated
2023/10/19 02:49:10 llama.go:438: llama runner stopped with error: exit status 1
2023/10/19 02:49:10 llama.go:356: starting llama runner
2023/10/19 02:49:10 llama.go:408: waiting for llama runner to start responding
{"timestamp":1697683750,"level":"WARNING","function":"server_params_parse","line":874,"message":"Not compiled with GPU offload support, --n-gpu-layers option will be ignored. See main README.md for information on enabling GPU BLAS support","n_gpu_layers":-1}
{"timestamp":1697683750,"level":"INFO","function":"main","line":1294,"message":"build info","build":74,"commit":"bc9d3e3"}
{"timestamp":1697683750,"level":"INFO","function":"main","line":1296,"message":"system info","n_threads":2,"total_threads":2,"system_info":"AVX = 1 | AVX2 = 1 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 1 | NEON = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 0 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | "}
llama_model_loader: loaded meta data with 20 key-value pairs and 291 tensors from /root/.ollama/models/blobs/sha256:6ae28029995007a3ee8d0b8556d50f3b59b831074cf19c84de87acf51fb54054 (version GGUF V2 (latest))
llama_model_loader: - tensor    0:                token_embd.weight q4_0     [  4096, 32000,     1,     1 ]
llama_model_loader: - tensor    1:              blk.0.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor    2:              blk.0.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor    3:              blk.0.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor    4:         blk.0.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor    5:            blk.0.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor    6:              blk.0.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor    7:            blk.0.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor    8:           blk.0.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor    9:            blk.0.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   10:              blk.1.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   11:              blk.1.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   12:              blk.1.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   13:         blk.1.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   14:            blk.1.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   15:              blk.1.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   16:            blk.1.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor   17:           blk.1.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   18:            blk.1.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   19:              blk.2.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   20:              blk.2.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   21:              blk.2.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   22:         blk.2.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   23:            blk.2.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   24:              blk.2.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   25:            blk.2.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor   26:           blk.2.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   27:            blk.2.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   28:              blk.3.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   29:              blk.3.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   30:              blk.3.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   31:         blk.3.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   32:            blk.3.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   33:              blk.3.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   34:            blk.3.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor   35:           blk.3.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   36:            blk.3.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   37:              blk.4.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   38:              blk.4.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   39:              blk.4.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   40:         blk.4.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   41:            blk.4.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   42:              blk.4.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   43:            blk.4.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor   44:           blk.4.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   45:            blk.4.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   46:              blk.5.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   47:              blk.5.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   48:              blk.5.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   49:         blk.5.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   50:            blk.5.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   51:              blk.5.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   52:            blk.5.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor   53:           blk.5.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   54:            blk.5.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   55:              blk.6.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   56:              blk.6.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   57:              blk.6.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   58:         blk.6.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   59:            blk.6.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   60:              blk.6.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   61:            blk.6.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor   62:           blk.6.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   63:            blk.6.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   64:              blk.7.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   65:              blk.7.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   66:              blk.7.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   67:         blk.7.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   68:            blk.7.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   69:              blk.7.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   70:            blk.7.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor   71:           blk.7.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   72:            blk.7.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   73:              blk.8.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   74:              blk.8.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   75:              blk.8.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   76:         blk.8.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   77:            blk.8.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   78:              blk.8.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   79:            blk.8.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor   80:           blk.8.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   81:            blk.8.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   82:              blk.9.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   83:              blk.9.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   84:              blk.9.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   85:         blk.9.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   86:            blk.9.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   87:              blk.9.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   88:            blk.9.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor   89:           blk.9.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   90:            blk.9.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   91:             blk.10.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   92:             blk.10.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   93:             blk.10.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   94:        blk.10.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   95:           blk.10.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   96:             blk.10.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   97:           blk.10.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor   98:          blk.10.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   99:           blk.10.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  100:             blk.11.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  101:             blk.11.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  102:             blk.11.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  103:        blk.11.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  104:           blk.11.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  105:             blk.11.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  106:           blk.11.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  107:          blk.11.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  108:           blk.11.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  109:             blk.12.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  110:             blk.12.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  111:             blk.12.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  112:        blk.12.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  113:           blk.12.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  114:             blk.12.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  115:           blk.12.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  116:          blk.12.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  117:           blk.12.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  118:             blk.13.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  119:             blk.13.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  120:             blk.13.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  121:        blk.13.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  122:           blk.13.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  123:             blk.13.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  124:           blk.13.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  125:          blk.13.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  126:           blk.13.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  127:             blk.14.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  128:             blk.14.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  129:             blk.14.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  130:        blk.14.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  131:           blk.14.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  132:             blk.14.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  133:           blk.14.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  134:          blk.14.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  135:           blk.14.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  136:             blk.15.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  137:             blk.15.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  138:             blk.15.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  139:        blk.15.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  140:           blk.15.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  141:             blk.15.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  142:           blk.15.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  143:          blk.15.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  144:           blk.15.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  145:             blk.16.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  146:             blk.16.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  147:             blk.16.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  148:        blk.16.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  149:           blk.16.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  150:             blk.16.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  151:           blk.16.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  152:          blk.16.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  153:           blk.16.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  154:             blk.17.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  155:             blk.17.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  156:             blk.17.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  157:        blk.17.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  158:           blk.17.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  159:             blk.17.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  160:           blk.17.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  161:          blk.17.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  162:           blk.17.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  163:             blk.18.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  164:             blk.18.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  165:             blk.18.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  166:        blk.18.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  167:           blk.18.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  168:             blk.18.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  169:           blk.18.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  170:          blk.18.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  171:           blk.18.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  172:             blk.19.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  173:             blk.19.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  174:             blk.19.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  175:        blk.19.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  176:           blk.19.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  177:             blk.19.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  178:           blk.19.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  179:          blk.19.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  180:           blk.19.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  181:             blk.20.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  182:             blk.20.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  183:             blk.20.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  184:        blk.20.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  185:           blk.20.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  186:             blk.20.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  187:           blk.20.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  188:          blk.20.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  189:           blk.20.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  190:             blk.21.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  191:             blk.21.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  192:             blk.21.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  193:        blk.21.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  194:           blk.21.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  195:             blk.21.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  196:           blk.21.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  197:          blk.21.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  198:           blk.21.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  199:             blk.22.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  200:             blk.22.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  201:             blk.22.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  202:        blk.22.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  203:           blk.22.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  204:             blk.22.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  205:           blk.22.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  206:          blk.22.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  207:           blk.22.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  208:             blk.23.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  209:             blk.23.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  210:             blk.23.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  211:        blk.23.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  212:           blk.23.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  213:             blk.23.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  214:           blk.23.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  215:          blk.23.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  216:           blk.23.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  217:             blk.24.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  218:             blk.24.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  219:             blk.24.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  220:        blk.24.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  221:           blk.24.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  222:             blk.24.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  223:           blk.24.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  224:          blk.24.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  225:           blk.24.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  226:             blk.25.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  227:             blk.25.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  228:             blk.25.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  229:        blk.25.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  230:           blk.25.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  231:             blk.25.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  232:           blk.25.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  233:          blk.25.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  234:           blk.25.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  235:             blk.26.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  236:             blk.26.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  237:             blk.26.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  238:        blk.26.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  239:           blk.26.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  240:             blk.26.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  241:           blk.26.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  242:          blk.26.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  243:           blk.26.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  244:             blk.27.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  245:             blk.27.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  246:             blk.27.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  247:        blk.27.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  248:           blk.27.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  249:             blk.27.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  250:           blk.27.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  251:          blk.27.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  252:           blk.27.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  253:             blk.28.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  254:             blk.28.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  255:             blk.28.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  256:        blk.28.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  257:           blk.28.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  258:             blk.28.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  259:           blk.28.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  260:          blk.28.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  261:           blk.28.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  262:             blk.29.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  263:             blk.29.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  264:             blk.29.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  265:        blk.29.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  266:           blk.29.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  267:             blk.29.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  268:           blk.29.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  269:          blk.29.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  270:           blk.29.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  271:             blk.30.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  272:             blk.30.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  273:             blk.30.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  274:        blk.30.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  275:           blk.30.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  276:             blk.30.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  277:           blk.30.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  278:          blk.30.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  279:           blk.30.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  280:             blk.31.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  281:             blk.31.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  282:             blk.31.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  283:        blk.31.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  284:           blk.31.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  285:             blk.31.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  286:           blk.31.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  287:          blk.31.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  288:           blk.31.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  289:               output_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  290:                    output.weight q6_K     [  4096, 32000,     1,     1 ]
llama_model_loader: - kv   0:                       general.architecture str     
llama_model_loader: - kv   1:                               general.name str     
llama_model_loader: - kv   2:                       llama.context_length u32     
llama_model_loader: - kv   3:                     llama.embedding_length u32     
llama_model_loader: - kv   4:                          llama.block_count u32     
llama_model_loader: - kv   5:                  llama.feed_forward_length u32     
llama_model_loader: - kv   6:                 llama.rope.dimension_count u32     
llama_model_loader: - kv   7:                 llama.attention.head_count u32     
llama_model_loader: - kv   8:              llama.attention.head_count_kv u32     
llama_model_loader: - kv   9:     llama.attention.layer_norm_rms_epsilon f32     
llama_model_loader: - kv  10:                       llama.rope.freq_base f32     
llama_model_loader: - kv  11:                          general.file_type u32     
llama_model_loader: - kv  12:                       tokenizer.ggml.model str     
llama_model_loader: - kv  13:                      tokenizer.ggml.tokens arr     
llama_model_loader: - kv  14:                      tokenizer.ggml.scores arr     
llama_model_loader: - kv  15:                  tokenizer.ggml.token_type arr     
llama_model_loader: - kv  16:                tokenizer.ggml.bos_token_id u32     
llama_model_loader: - kv  17:                tokenizer.ggml.eos_token_id u32     
llama_model_loader: - kv  18:            tokenizer.ggml.unknown_token_id u32     
llama_model_loader: - kv  19:               general.quantization_version u32     
llama_model_loader: - type  f32:   65 tensors
llama_model_loader: - type q4_0:  225 tensors
llama_model_loader: - type q6_K:    1 tensors
llm_load_print_meta: format         = GGUF V2 (latest)
llm_load_print_meta: arch           = llama
llm_load_print_meta: vocab type     = SPM
llm_load_print_meta: n_vocab        = 32000
llm_load_print_meta: n_merges       = 0
llm_load_print_meta: n_ctx_train    = 32768
llm_load_print_meta: n_ctx          = 2048
llm_load_print_meta: n_embd         = 4096
llm_load_print_meta: n_head         = 32
llm_load_print_meta: n_head_kv      = 8
llm_load_print_meta: n_layer        = 32
llm_load_print_meta: n_rot          = 128
llm_load_print_meta: n_gqa          = 4
llm_load_print_meta: f_norm_eps     = 0.0e+00
llm_load_print_meta: f_norm_rms_eps = 1.0e-05
llm_load_print_meta: n_ff           = 14336
llm_load_print_meta: freq_base      = 10000.0
llm_load_print_meta: freq_scale     = 1
llm_load_print_meta: model type     = 7B
llm_load_print_meta: model ftype    = mostly Q4_0
llm_load_print_meta: model params   = 7.24 B
llm_load_print_meta: model size     = 3.83 GiB (4.54 BPW) 
llm_load_print_meta: general.name   = mistralai
llm_load_print_meta: BOS token = 1 '<s>'
llm_load_print_meta: EOS token = 2 '</s>'
llm_load_print_meta: UNK token = 0 '<unk>'
llm_load_print_meta: LF token  = 13 '<0x0A>'
llm_load_tensors: ggml ctx size =    0.09 MB
llm_load_tensors: mem required  = 3917.96 MB (+  256.00 MB per state)

image

<!-- gh-comment-id:1769808358 --> @tranhoangnguyen03 commented on GitHub (Oct 19, 2023): Below is the full reading after I ran `ollama run mistral`. It looks like an issue with the default Ollama CUDA driver ``` 2023/10/19 02:47:55 images.go:995: total blobs: 0 2023/10/19 02:47:55 images.go:1002: total unused blobs removed: 0 2023/10/19 02:47:55 routes.go:614: Listening on 127.0.0.1:11434 2023/10/19 02:48:02 images.go:995: total blobs: 0 2023/10/19 02:48:02 images.go:1002: total unused blobs removed: 0 2023/10/19 02:48:02 routes.go:614: Listening on 127.0.0.1:11434 [GIN] 2023/10/19 - 02:48:23 | 200 | 1.818527ms | 127.0.0.1 | HEAD "/" [GIN] 2023/10/19 - 02:48:23 | 200 | 276.108µs | 127.0.0.1 | GET "/api/tags" 2023/10/19 02:48:25 download.go:126: downloading 6ae280299950 in 64 64 MB part(s) 2023/10/19 02:48:47 download.go:126: downloading fede2d8d6c1f in 1 29 B part(s) 2023/10/19 02:48:50 download.go:126: downloading b96850d2e482 in 1 307 B part(s) [GIN] 2023/10/19 - 02:49:08 | 200 | 45.31729643s | 127.0.0.1 | POST "/api/pull" 2023/10/19 02:49:10 llama.go:252: 15101 MiB VRAM available, loading up to 113 GPU layers 2023/10/19 02:49:10 llama.go:356: starting llama runner 2023/10/19 02:49:10 llama.go:408: waiting for llama runner to start responding CUDA error 35 at /go/src/github.com/jmorganca/ollama/llm/llama.cpp/gguf/ggml-cuda.cu:5522: CUDA driver version is insufficient for CUDA runtime version current device: -502659984 2023/10/19 02:49:10 llama.go:373: error starting llama runner: llama runner process has terminated 2023/10/19 02:49:10 llama.go:438: llama runner stopped with error: exit status 1 2023/10/19 02:49:10 llama.go:356: starting llama runner 2023/10/19 02:49:10 llama.go:408: waiting for llama runner to start responding {"timestamp":1697683750,"level":"WARNING","function":"server_params_parse","line":874,"message":"Not compiled with GPU offload support, --n-gpu-layers option will be ignored. See main README.md for information on enabling GPU BLAS support","n_gpu_layers":-1} {"timestamp":1697683750,"level":"INFO","function":"main","line":1294,"message":"build info","build":74,"commit":"bc9d3e3"} {"timestamp":1697683750,"level":"INFO","function":"main","line":1296,"message":"system info","n_threads":2,"total_threads":2,"system_info":"AVX = 1 | AVX2 = 1 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 1 | NEON = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 0 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | "} llama_model_loader: loaded meta data with 20 key-value pairs and 291 tensors from /root/.ollama/models/blobs/sha256:6ae28029995007a3ee8d0b8556d50f3b59b831074cf19c84de87acf51fb54054 (version GGUF V2 (latest)) llama_model_loader: - tensor 0: token_embd.weight q4_0 [ 4096, 32000, 1, 1 ] llama_model_loader: - tensor 1: blk.0.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 2: blk.0.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 3: blk.0.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 4: blk.0.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 5: blk.0.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 6: blk.0.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 7: blk.0.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 8: blk.0.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 9: blk.0.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 10: blk.1.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 11: blk.1.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 12: blk.1.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 13: blk.1.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 14: blk.1.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 15: blk.1.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 16: blk.1.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 17: blk.1.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 18: blk.1.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 19: blk.2.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 20: blk.2.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 21: blk.2.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 22: blk.2.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 23: blk.2.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 24: blk.2.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 25: blk.2.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 26: blk.2.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 27: blk.2.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 28: blk.3.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 29: blk.3.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 30: blk.3.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 31: blk.3.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 32: blk.3.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 33: blk.3.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 34: blk.3.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 35: blk.3.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 36: blk.3.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 37: blk.4.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 38: blk.4.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 39: blk.4.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 40: blk.4.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 41: blk.4.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 42: blk.4.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 43: blk.4.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 44: blk.4.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 45: blk.4.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 46: blk.5.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 47: blk.5.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 48: blk.5.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 49: blk.5.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 50: blk.5.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 51: blk.5.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 52: blk.5.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 53: blk.5.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 54: blk.5.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 55: blk.6.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 56: blk.6.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 57: blk.6.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 58: blk.6.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 59: blk.6.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 60: blk.6.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 61: blk.6.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 62: blk.6.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 63: blk.6.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 64: blk.7.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 65: blk.7.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 66: blk.7.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 67: blk.7.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 68: blk.7.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 69: blk.7.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 70: blk.7.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 71: blk.7.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 72: blk.7.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 73: blk.8.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 74: blk.8.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 75: blk.8.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 76: blk.8.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 77: blk.8.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 78: blk.8.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 79: blk.8.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 80: blk.8.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 81: blk.8.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 82: blk.9.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 83: blk.9.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 84: blk.9.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 85: blk.9.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 86: blk.9.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 87: blk.9.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 88: blk.9.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 89: blk.9.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 90: blk.9.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 91: blk.10.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 92: blk.10.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 93: blk.10.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 94: blk.10.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 95: blk.10.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 96: blk.10.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 97: blk.10.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 98: blk.10.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 99: blk.10.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 100: blk.11.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 101: blk.11.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 102: blk.11.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 103: blk.11.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 104: blk.11.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 105: blk.11.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 106: blk.11.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 107: blk.11.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 108: blk.11.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 109: blk.12.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 110: blk.12.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 111: blk.12.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 112: blk.12.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 113: blk.12.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 114: blk.12.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 115: blk.12.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 116: blk.12.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 117: blk.12.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 118: blk.13.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 119: blk.13.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 120: blk.13.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 121: blk.13.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 122: blk.13.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 123: blk.13.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 124: blk.13.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 125: blk.13.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 126: blk.13.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 127: blk.14.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 128: blk.14.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 129: blk.14.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 130: blk.14.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 131: blk.14.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 132: blk.14.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 133: blk.14.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 134: blk.14.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 135: blk.14.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 136: blk.15.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 137: blk.15.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 138: blk.15.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 139: blk.15.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 140: blk.15.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 141: blk.15.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 142: blk.15.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 143: blk.15.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 144: blk.15.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 145: blk.16.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 146: blk.16.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 147: blk.16.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 148: blk.16.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 149: blk.16.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 150: blk.16.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 151: blk.16.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 152: blk.16.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 153: blk.16.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 154: blk.17.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 155: blk.17.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 156: blk.17.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 157: blk.17.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 158: blk.17.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 159: blk.17.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 160: blk.17.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 161: blk.17.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 162: blk.17.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 163: blk.18.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 164: blk.18.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 165: blk.18.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 166: blk.18.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 167: blk.18.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 168: blk.18.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 169: blk.18.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 170: blk.18.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 171: blk.18.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 172: blk.19.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 173: blk.19.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 174: blk.19.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 175: blk.19.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 176: blk.19.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 177: blk.19.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 178: blk.19.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 179: blk.19.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 180: blk.19.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 181: blk.20.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 182: blk.20.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 183: blk.20.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 184: blk.20.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - 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tensor 289: output_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 290: output.weight q6_K [ 4096, 32000, 1, 1 ] llama_model_loader: - kv 0: general.architecture str llama_model_loader: - kv 1: general.name str llama_model_loader: - kv 2: llama.context_length u32 llama_model_loader: - kv 3: llama.embedding_length u32 llama_model_loader: - kv 4: llama.block_count u32 llama_model_loader: - kv 5: llama.feed_forward_length u32 llama_model_loader: - kv 6: llama.rope.dimension_count u32 llama_model_loader: - kv 7: llama.attention.head_count u32 llama_model_loader: - kv 8: llama.attention.head_count_kv u32 llama_model_loader: - kv 9: llama.attention.layer_norm_rms_epsilon f32 llama_model_loader: - kv 10: llama.rope.freq_base f32 llama_model_loader: - kv 11: general.file_type u32 llama_model_loader: - kv 12: tokenizer.ggml.model str llama_model_loader: - kv 13: tokenizer.ggml.tokens arr llama_model_loader: - kv 14: tokenizer.ggml.scores arr llama_model_loader: - kv 15: tokenizer.ggml.token_type arr llama_model_loader: - kv 16: tokenizer.ggml.bos_token_id u32 llama_model_loader: - kv 17: tokenizer.ggml.eos_token_id u32 llama_model_loader: - kv 18: tokenizer.ggml.unknown_token_id u32 llama_model_loader: - kv 19: general.quantization_version u32 llama_model_loader: - type f32: 65 tensors llama_model_loader: - type q4_0: 225 tensors llama_model_loader: - type q6_K: 1 tensors llm_load_print_meta: format = GGUF V2 (latest) llm_load_print_meta: arch = llama llm_load_print_meta: vocab type = SPM llm_load_print_meta: n_vocab = 32000 llm_load_print_meta: n_merges = 0 llm_load_print_meta: n_ctx_train = 32768 llm_load_print_meta: n_ctx = 2048 llm_load_print_meta: n_embd = 4096 llm_load_print_meta: n_head = 32 llm_load_print_meta: n_head_kv = 8 llm_load_print_meta: n_layer = 32 llm_load_print_meta: n_rot = 128 llm_load_print_meta: n_gqa = 4 llm_load_print_meta: f_norm_eps = 0.0e+00 llm_load_print_meta: f_norm_rms_eps = 1.0e-05 llm_load_print_meta: n_ff = 14336 llm_load_print_meta: freq_base = 10000.0 llm_load_print_meta: freq_scale = 1 llm_load_print_meta: model type = 7B llm_load_print_meta: model ftype = mostly Q4_0 llm_load_print_meta: model params = 7.24 B llm_load_print_meta: model size = 3.83 GiB (4.54 BPW) llm_load_print_meta: general.name = mistralai llm_load_print_meta: BOS token = 1 '<s>' llm_load_print_meta: EOS token = 2 '</s>' llm_load_print_meta: UNK token = 0 '<unk>' llm_load_print_meta: LF token = 13 '<0x0A>' llm_load_tensors: ggml ctx size = 0.09 MB llm_load_tensors: mem required = 3917.96 MB (+ 256.00 MB per state) ``` ![image](https://github.com/jmorganca/ollama/assets/31383641/7e3245b1-0dd7-4258-8ae2-8078e7efd71d)
GiteaMirror commented 2026-04-22 02:12:51 -05:00
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@missandi commented on GitHub (Oct 19, 2023):

I tested in google colab T4 but run so slow, maybe it's not using GPU 👎

<!-- gh-comment-id:1770671258 --> @missandi commented on GitHub (Oct 19, 2023): I tested in google colab T4 but run so slow, maybe it's not using GPU 👎
GiteaMirror commented 2026-04-22 02:12:51 -05:00
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@tranhoangnguyen03 commented on GitHub (Oct 19, 2023):

I beg to differ. My llama.cpp FastAPI server runs very fast on T4 GPU (around 20 tokens per sec with Mistral-Instruct) whereas Ollama server runs at 1-3 tokens per sec for me.

GPU makes a big difference.

<!-- gh-comment-id:1771016713 --> @tranhoangnguyen03 commented on GitHub (Oct 19, 2023): I beg to differ. My llama.cpp FastAPI server runs very fast on T4 GPU (around 20 tokens per sec with Mistral-Instruct) whereas Ollama server runs at 1-3 tokens per sec for me. GPU makes a big difference.
GiteaMirror commented 2026-04-22 02:12:52 -05:00
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@missandi commented on GitHub (Oct 19, 2023):

GPU

How to using GPU in it (only change runtime to T4 or install more driver ?)

<!-- gh-comment-id:1771369460 --> @missandi commented on GitHub (Oct 19, 2023): > GPU How to using GPU in it (only change runtime to T4 or install more driver ?)
GiteaMirror commented 2026-04-22 02:12:52 -05:00
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@mxyng commented on GitHub (Oct 19, 2023):

CUDA error 35 at /go/src/github.com/jmorganca/ollama/llm/llama.cpp/gguf/ggml-cuda.cu:5522: CUDA driver version is insufficient for CUDA runtime version

This error causes ollama to fallback to CPU-only. What CUDA version does this instance use? For compatiblity, Ollama uses CUDA 11.8

<!-- gh-comment-id:1771465341 --> @mxyng commented on GitHub (Oct 19, 2023): > CUDA error 35 at /go/src/github.com/jmorganca/ollama/llm/llama.cpp/gguf/ggml-cuda.cu:5522: CUDA driver version is insufficient for CUDA runtime version This error causes ollama to fallback to CPU-only. What CUDA version does this instance use? For compatiblity, Ollama uses CUDA 11.8
GiteaMirror commented 2026-04-22 02:12:52 -05:00
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@mxyng commented on GitHub (Oct 19, 2023):

See #758.

CUDA drivers need to be updated in order for Ollama to use GPU in Colab. Update it with this

!sudo apt-get update && sudo apt-get install -y cuda-drivers
<!-- gh-comment-id:1771768264 --> @mxyng commented on GitHub (Oct 19, 2023): See #758. CUDA drivers need to be updated in order for Ollama to use GPU in Colab. Update it with this ``` !sudo apt-get update && sudo apt-get install -y cuda-drivers ```
GiteaMirror commented 2026-04-22 02:12:53 -05:00
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@missandi commented on GitHub (Oct 20, 2023):

See #758.

CUDA drivers need to be updated in order for Ollama to use GPU in Colab. Update it with this

!sudo apt-get update && sudo apt-get install -y cuda-drivers

*** Reboot your computer and verify that the NVIDIA graphics driver can ***
*** be loaded. ***

Have you know how can restart colab after install cuda-drivers?

<!-- gh-comment-id:1771977353 --> @missandi commented on GitHub (Oct 20, 2023): > See #758. > > CUDA drivers need to be updated in order for Ollama to use GPU in Colab. Update it with this > > ``` > !sudo apt-get update && sudo apt-get install -y cuda-drivers > ``` ***************************************************************************** *** Reboot your computer and verify that the NVIDIA graphics driver can *** *** be loaded. *** ***************************************************************************** Have you know how can restart colab after install cuda-drivers?
GiteaMirror commented 2026-04-22 02:12:53 -05:00
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@missandi commented on GitHub (Oct 20, 2023):

@tranhoangnguyen03
Bro I have one question want to ask you. I using free account and have this issue after using GPU:
You cannot currently connect to a GPU due to usage limits in Colab
Once account google can using limit how much times and limit about how many days will turn again ?

<!-- gh-comment-id:1772350590 --> @missandi commented on GitHub (Oct 20, 2023): @tranhoangnguyen03 Bro I have one question want to ask you. I using free account and have this issue after using GPU: `You cannot currently connect to a GPU due to usage limits in Colab` Once account google can using limit how much times and limit about how many days will turn again ?
GiteaMirror commented 2026-04-22 02:12:54 -05:00
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@tranhoangnguyen03 commented on GitHub (Oct 20, 2023):

Free accounts are not guaranteed a GPU instance. Recently a lot of people started using Colab to host Stable Diffusion models which often cause shortage of Colab GPU. You should subscribe to Pro if you want consistent GPU availability.

<!-- gh-comment-id:1772355088 --> @tranhoangnguyen03 commented on GitHub (Oct 20, 2023): Free accounts are not guaranteed a GPU instance. Recently a lot of people started using Colab to host Stable Diffusion models which often cause shortage of Colab GPU. You should subscribe to Pro if you want consistent GPU availability.
GiteaMirror commented 2026-04-22 02:12:54 -05:00
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@missandi commented on GitHub (Oct 20, 2023):

@tranhoangnguyen03 Thank you for your inquiry. In regards to the Pro account priced at $10 per month, I would like to confirm whether it provides unlimited GPU time. This is of particular importance to me as some of my tasks require continuous background processing for 4 to 8 hours each day.

<!-- gh-comment-id:1772365890 --> @missandi commented on GitHub (Oct 20, 2023): @tranhoangnguyen03 Thank you for your inquiry. In regards to the Pro account priced at $10 per month, I would like to confirm whether it provides unlimited GPU time. This is of particular importance to me as some of my tasks require continuous background processing for 4 to 8 hours each day.
GiteaMirror commented 2026-04-22 02:12:55 -05:00
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@tranhoangnguyen03 commented on GitHub (Oct 20, 2023):

Wrong place to discuss this. I suggest you go to Reddit.

<!-- gh-comment-id:1772367454 --> @tranhoangnguyen03 commented on GitHub (Oct 20, 2023): Wrong place to discuss this. I suggest you go to Reddit.
GiteaMirror commented 2026-04-22 02:12:55 -05:00
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@darkBuddha commented on GitHub (Oct 25, 2023):

What is the minimum CUDA compute capability? I get CUDA error 209 at /go/src/github.com/jmorganca/ollama/llm/llama.cpp/gguf/ggml-cuda.cu:6591: no kernel image is available for execution on the device on my K2200 with CC 5.0

<!-- gh-comment-id:1778954772 --> @darkBuddha commented on GitHub (Oct 25, 2023): What is the minimum CUDA compute capability? I get `CUDA error 209 at /go/src/github.com/jmorganca/ollama/llm/llama.cpp/gguf/ggml-cuda.cu:6591: no kernel image is available for execution on the device` on my K2200 with CC 5.0
GiteaMirror commented 2026-04-22 02:12:56 -05:00
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@mxyng commented on GitHub (Oct 25, 2023):

Have you know how can restart colab after install cuda-drivers?

While it says that in the install outputs, it doesn't seem to require a restart. Starting ollama immediately afterwards should use the GPU

<!-- gh-comment-id:1779908521 --> @mxyng commented on GitHub (Oct 25, 2023): > Have you know how can restart colab after install cuda-drivers? While it says that in the install outputs, it doesn't seem to require a restart. Starting ollama immediately afterwards should use the GPU
GiteaMirror commented 2026-04-22 02:12:56 -05:00
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@mxyng commented on GitHub (Oct 25, 2023):

What is the minimum CUDA compute capability? I get CUDA error 209 at /go/src/github.com/jmorganca/ollama/llm/llama.cpp/gguf/ggml-cuda.cu:6591: no kernel image is available for execution on the device on my K2200 with CC 5.0

Ollama targets CUDA 11.8 which should be compatible with most GPUs NVIDIA currently supports.

<!-- gh-comment-id:1779916722 --> @mxyng commented on GitHub (Oct 25, 2023): > What is the minimum CUDA compute capability? I get `CUDA error 209 at /go/src/github.com/jmorganca/ollama/llm/llama.cpp/gguf/ggml-cuda.cu:6591: no kernel image is available for execution on the device` on my K2200 with CC 5.0 Ollama targets CUDA 11.8 which should be compatible with most GPUs NVIDIA currently supports.
GiteaMirror commented 2026-04-22 02:12:57 -05:00
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@mxyng commented on GitHub (Oct 25, 2023):

I'm closing this as a duplicate of #758. Please move any additional comment into that issue

<!-- gh-comment-id:1779918864 --> @mxyng commented on GitHub (Oct 25, 2023): I'm closing this as a duplicate of #758. Please move any additional comment into that issue
GiteaMirror commented 2026-04-22 02:12:58 -05:00
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@Arslan-Mehmood1 commented on GitHub (Nov 19, 2024):

follow https://medium.com/@abonia/running-ollama-in-google-colab-free-tier-545609258453

<!-- gh-comment-id:2485851266 --> @Arslan-Mehmood1 commented on GitHub (Nov 19, 2024): follow https://medium.com/@abonia/running-ollama-in-google-colab-free-tier-545609258453
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