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[GH-ISSUE #4529] error loading model: error loading model vocabulary: unknown pre-tokenizer type: 'qwen2' #49351
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opened 2026-04-28 11:26:07 -05:00 by GiteaMirror
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Reference: github-starred/ollama#49351
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Originally created by @Anorid on GitHub (May 20, 2024).
Original GitHub issue: https://github.com/ollama/ollama/issues/4529
What is the issue?
I carefully read the contents of the readme's documentation to try and found that something went wrong
time=2024-05-20T10:06:02.688+08:00 level=INFO source=server.go:320 msg="starting llama server" cmd="/tmp/ollama2132883000/runners/cuda_v11/ollama_llama_server --model /root/autodl-tmp/models/blobs/sha256-1c751709783923dab2b876d5c5c2ca36d4e205cfef7d88988df45752cb91f245 --ctx-size 2048 --batch-size 512 --embedding --log-disable --n-gpu-layers 41 --parallel 1 --port 33525"
time=2024-05-20T10:06:02.690+08:00 level=INFO source=sched.go:338 msg="loaded runners" count=1
time=2024-05-20T10:06:02.690+08:00 level=INFO source=server.go:504 msg="waiting for llama runner to start responding"
time=2024-05-20T10:06:02.691+08:00 level=INFO source=server.go:540 msg="waiting for server to become available" status="llm server error"
INFO [main] build info | build=1 commit="952d03d" tid="140401842012160" timestamp=1716170762
INFO [main] system info | n_threads=64 n_threads_batch=-1 system_info="AVX = 1 | AVX_VNNI = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 0 | NEON = 0 | ARM_FMA = 0 | F16C = 0 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 | " tid="140401842012160" timestamp=1716170762 total_threads=128
INFO [main] HTTP server listening | hostname="127.0.0.1" n_threads_http="127" port="33525" tid="140401842012160" timestamp=1716170762
llama_model_loader: loaded meta data with 21 key-value pairs and 483 tensors from /root/autodl-tmp/models/blobs/sha256-1c751709783923dab2b876d5c5c2ca36d4e205cfef7d88988df45752cb91f245 (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = qwen2
llama_model_loader: - kv 1: general.name str = merge5-1
llama_model_loader: - kv 2: qwen2.block_count u32 = 40
llama_model_loader: - kv 3: qwen2.context_length u32 = 32768
llama_model_loader: - kv 4: qwen2.embedding_length u32 = 5120
llama_model_loader: - kv 5: qwen2.feed_forward_length u32 = 13696
llama_model_loader: - kv 6: qwen2.attention.head_count u32 = 40
llama_model_loader: - kv 7: qwen2.attention.head_count_kv u32 = 40
llama_model_loader: - kv 8: qwen2.rope.freq_base f32 = 1000000.000000
llama_model_loader: - kv 9: qwen2.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 10: general.file_type u32 = 2
llama_model_loader: - kv 11: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 12: tokenizer.ggml.pre str = qwen2
llama_model_loader: - kv 13: tokenizer.ggml.tokens arr[str,152064] = ["!", """, "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 14: tokenizer.ggml.token_type arr[i32,152064] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 15: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv 16: tokenizer.ggml.eos_token_id u32 = 151643
llama_model_loader: - kv 17: tokenizer.ggml.padding_token_id u32 = 151643
llama_model_loader: - kv 18: tokenizer.ggml.bos_token_id u32 = 151643
llama_model_loader: - kv 19: tokenizer.chat_template str = {% for message in messages %}{% if lo...
llama_model_loader: - kv 20: general.quantization_version u32 = 2
llama_model_loader: - type f32: 201 tensors
llama_model_loader: - type q4_0: 281 tensors
llama_model_loader: - type q6_K: 1 tensors
time=2024-05-20T10:06:02.944+08:00 level=INFO source=server.go:540 msg="waiting for server to become available" status="llm server loading model"
llama_model_load: error loading model: error loading model vocabulary: unknown pre-tokenizer type: 'qwen2'
llama_load_model_from_file: exception loading model
terminate called after throwing an instance of 'std::runtime_error'
what(): error loading model vocabulary: unknown pre-tokenizer type: 'qwen2'
time=2024-05-20T10:06:03.285+08:00 level=INFO source=server.go:540 msg="waiting for server to become available" status="llm server error"
time=2024-05-20T10:06:03.535+08:00 level=ERROR source=sched.go:344 msg="error loading llama server" error="llama runner process has terminated: signal: aborted (core dumped) "
[GIN] 2024/05/20 - 10:06:03 | 500 | 2.178464527s | 127.0.0.1 | POST "/api/chat"
time=2024-05-20T10:06:07.831+08:00 level=INFO source=memory.go:133 msg="offload to gpu" layers.requested=-1 layers.real=41 memory.available="47.3 GiB" memory.required.full="9.7 GiB" memory.required.partial="9.7 GiB" memory.required.kv="1.6 GiB" memory.weights.total="7.2 GiB" memory.weights.repeating="6.6 GiB" memory.weights.nonrepeating="609.1 MiB" memory.graph.full="307.0 MiB" memory.graph.partial="916.1 MiB"
time=2024-05-20T10:06:07.832+08:00 level=INFO source=memory.go:133 msg="offload to gpu" layers.requested=-1 layers.real=41 memory.available="47.3 GiB" memory.required.full="9.7 GiB" memory.required.partial="9.7 GiB" memory.required.kv="1.6 GiB" memory.weights.total="7.2 GiB" memory.weights.repeating="6.6 GiB" memory.weights.nonrepeating="609.1 MiB" memory.graph.full="307.0 MiB" memory.graph.partial="916.1 MiB"
time=2024-05-20T10:06:07.832+08:00 level=INFO source=server.go:320 msg="starting llama server" cmd="/tmp/ollama2132883000/runners/cuda_v11/ollama_llama_server --model /root/autodl-tmp/models/blobs/sha256-1c751709783923dab2b876d5c5c2ca36d4e205cfef7d88988df45752cb91f245 --ctx-size 2048 --batch-size 512 --embedding --log-disable --n-gpu-layers 41 --parallel 1 --port 43339"
time=2024-05-20T10:06:07.833+08:00 level=INFO source=sched.go:338 msg="loaded runners" count=1
time=2024-05-20T10:06:07.833+08:00 level=INFO source=server.go:504 msg="waiting for llama runner to start responding"
time=2024-05-20T10:06:07.833+08:00 level=INFO source=server.go:540 msg="waiting for server to become available" status="llm server error"
INFO [main] build info | build=1 commit="952d03d" tid="140283378036736" timestamp=1716170767
INFO [main] system info | n_threads=64 n_threads_batch=-1 system_info="AVX = 1 | AVX_VNNI = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 0 | NEON = 0 | ARM_FMA = 0 | F16C = 0 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 | " tid="140283378036736" timestamp=1716170767 total_threads=128
INFO [main] HTTP server listening | hostname="127.0.0.1" n_threads_http="127" port="43339" tid="140283378036736" timestamp=1716170767
llama_model_loader: loaded meta data with 21 key-value pairs and 483 tensors from /root/autodl-tmp/models/blobs/sha256-1c751709783923dab2b876d5c5c2ca36d4e205cfef7d88988df45752cb91f245 (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = qwen2
llama_model_loader: - kv 1: general.name str = merge5-1
llama_model_loader: - kv 2: qwen2.block_count u32 = 40
llama_model_loader: - kv 3: qwen2.context_length u32 = 32768
llama_model_loader: - kv 4: qwen2.embedding_length u32 = 5120
llama_model_loader: - kv 5: qwen2.feed_forward_length u32 = 13696
llama_model_loader: - kv 6: qwen2.attention.head_count u32 = 40
llama_model_loader: - kv 7: qwen2.attention.head_count_kv u32 = 40
llama_model_loader: - kv 8: qwen2.rope.freq_base f32 = 1000000.000000
llama_model_loader: - kv 9: qwen2.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 10: general.file_type u32 = 2
llama_model_loader: - kv 11: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 12: tokenizer.ggml.pre str = qwen2
llama_model_loader: - kv 13: tokenizer.ggml.tokens arr[str,152064] = ["!", """, "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 14: tokenizer.ggml.token_type arr[i32,152064] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 15: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv 16: tokenizer.ggml.eos_token_id u32 = 151643
llama_model_loader: - kv 17: tokenizer.ggml.padding_token_id u32 = 151643
llama_model_loader: - kv 18: tokenizer.ggml.bos_token_id u32 = 151643
llama_model_loader: - kv 19: tokenizer.chat_template str = {% for message in messages %}{% if lo...
llama_model_loader: - kv 20: general.quantization_version u32 = 2
llama_model_loader: - type f32: 201 tensors
llama_model_loader: - type q4_0: 281 tensors
llama_model_loader: - type q6_K: 1 tensors
time=2024-05-20T10:06:08.085+08:00 level=INFO source=server.go:540 msg="waiting for server to become available" status="llm server loading model"
llama_model_load: error loading model: error loading model vocabulary: unknown pre-tokenizer type: 'qwen2'
llama_load_model_from_file: exception loading model
terminate called after throwing an instance of 'std::runtime_error'
what(): error loading model vocabulary: unknown pre-tokenizer type: 'qwen2'
time=2024-05-20T10:06:08.437+08:00 level=INFO source=server.go:540 msg="waiting for server to become available" status="llm server error"
time=2024-05-20T10:06:08.656+08:00 level=WARN source=sched.go:512 msg="gpu VRAM usage didn't recover within timeout" seconds=5.120574757
time=2024-05-20T10:06:08.688+08:00 level=ERROR source=sched.go:344 msg="error loading llama server" error="llama runner process has terminated: signal: aborted (core dumped) "
I look at the 4b to 72b of qwen1.5 provided, so this should be provided by the tokenizer as well
OS
Linux
GPU
Nvidia
CPU
Other
Ollama version
client version is 0.1.38
@Anorid commented on GitHub (May 20, 2024):
This is the GGUF file and the information for the imported model
@liduang commented on GitHub (May 20, 2024):
I have also encountered this problem, and I feel that it is the problem here:
May 20 17:54:48 localhost.localdomain ollama[11885]: llama_model_loader: - kv 12: tokenizer.ggml.pre str = qwen2It is estimated that there is a conflict with llama.cpp's update this time
7114
@GitTurboy commented on GitHub (May 21, 2024):
I got the same error on windows system:
llama_model_loader: loaded meta data with 21 key-value pairs and 291 tensors from D:\lamaModels\blobs\sha256-6b22d907af67d494c1194b1bd688423945b4d3009bded2e5ecbc88d426b0c5a3 (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = qwen2
llama_model_loader: - kv 1: general.name str = Qwen1___5-1___8B-Chat
llama_model_loader: - kv 2: qwen2.block_count u32 = 24
llama_model_loader: - kv 3: qwen2.context_length u32 = 32768
llama_model_loader: - kv 4: qwen2.embedding_length u32 = 2048
llama_model_loader: - kv 5: qwen2.feed_forward_length u32 = 5504
llama_model_loader: - kv 6: qwen2.attention.head_count u32 = 16
llama_model_loader: - kv 7: qwen2.attention.head_count_kv u32 = 16
llama_model_loader: - kv 8: qwen2.rope.freq_base f32 = 1000000.000000
llama_model_loader: - kv 9: qwen2.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 10: general.file_type u32 = 1
llama_model_loader: - kv 11: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 12: tokenizer.ggml.pre str = qwen2
llama_model_loader: - kv 13: tokenizer.ggml.tokens arr[str,151936] = ["!", """, "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 14: tokenizer.ggml.token_type arr[i32,151936] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 15: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv 16: tokenizer.ggml.eos_token_id u32 = 151645
llama_model_loader: - kv 17: tokenizer.ggml.padding_token_id u32 = 151643
llama_model_loader: - kv 18: tokenizer.ggml.bos_token_id u32 = 151643
llama_model_loader: - kv 19: tokenizer.chat_template str = {% for message in messages %}{% if lo...
llama_model_loader: - kv 20: general.quantization_version u32 = 2
llama_model_loader: - type f32: 121 tensors
llama_model_loader: - type f16: 170 tensors
time=2024-05-20T16:44:58.427+08:00 level=INFO source=server.go:540 msg="waiting for server to become available" status="llm server loading model"
llama_model_load: error loading model: error loading model vocabulary: unknown pre-tokenizer type: 'qwen2'
llama_load_model_from_file: exception loading model
time=2024-05-20T16:44:58.698+08:00 level=ERROR source=sched.go:344 msg="error loading llama server" error="llama runner process has terminated: exit status 0xc0000409 "
@binganao commented on GitHub (May 21, 2024):
临时解决方案可以参考我的,使用 convert-hf-to-gguf.py 合并模型时,注释掉这一行
@Treedy2020 commented on GitHub (May 21, 2024):
The specific reason may be that llama.cpp/convert-hf-to-gguf.py encountered issues during the rapid iteration process. I experienced the same problem when exporting and quantizing qwen2 in the latest version of llama.cpp, but the exported and quantized gguf models using an older version of llama.cpp for qwen2 are usable. You can try modifying this file like @binganao did, or simply roll back the version of llama.cpp and try again:
check this release for detail. Then import and re-quantize the modelscope / hf folder of qwen2 according to the official ollama documentation. Hopefully this can solve your problem.
@xianyuxm commented on GitHub (May 22, 2024):
I tried binganao's method, but it didn't work. However, following your suggestion to roll back to a previous version successfully resolved the issue. Thank you!
@bartowski1182 commented on GitHub (May 26, 2024):
I just tried a Qwen2 model I made recently with llama.cpp ./main and it loaded and generated with no issues. Are we sure this isn't ollama needing an update?
@tk19911120 commented on GitHub (May 26, 2024):
I have the same issue when exporting and quantizing qwen1.5-7b-chat,(Error: llama runner process has terminated: signal: aborted (core dumped)). And I tried Treedy2020's method(
sudo git reset --hard 46e12c4692a37bdd31a0432fc5153d7d22bc7f72), solved the issue.ollama version is 0.1.37
@pdevine commented on GitHub (May 30, 2024):
The problem was that llama.cpp changed how the tokenizer worked because of changes w/ llama3 tokenization. This should be fixed in
0.1.39though, so I'll go ahead and close the issue. @Anorid LMK if it's still persisting and I can reopen.@markg85 commented on GitHub (Jun 7, 2024):
Could this be re-opened?
I have the very same issue too.
Now there's something strange going on too.
While i have 0.1.41 installed (arch linux):
So upon further inspection, this is how it's build:
https://gitlab.archlinux.org/archlinux/packaging/packages/ollama/-/blob/main/PKGBUILD?ref_type=heads
Which builds the tag
476fb8e892, that is the 0.1.41 tag: https://github.com/ollama/ollama/releases/tag/v0.1.41The llama-cpp version is this tag
5921b8f089which is just a week old.Am i missing something here to get qwen2 working?
The version thing is weird for sure but that might be it's own bug?
@cyp0633 commented on GitHub (Jun 7, 2024):
Did you reboot your machine or do
sudo systemctl restart ollamaafter upgrading? The running ollama service is not automatically upgraded.@markg85 commented on GitHub (Jun 7, 2024):
@cyp0633 yes! :)
I did both (and a couple times), didn't help.
Let's not spend too much time in the version thing but let's check 1 thing.
Could someone else run
ollama --versionion a 0.1.41 release and post your result here? If there's anyone else that has this bug too (wrong version number for the release your using) then I'll make a new issue for that. If this can't be reproduced and the command matches your install then there's something seriously wrong on my setup and I'll have to dig deep to figure it out.@I321065 commented on GitHub (Jun 7, 2024):
same issue happened to me
@markg85 commented on GitHub (Jun 7, 2024):
Issue can be closed again.
I had installed ollama using the script on the ollama site.
And i had it installed through my package manager.
Removing the one installed through the script made things work. Version is as expected now.
100% user error, sorry for the noise!
@rallg0535 commented on GitHub (Jun 10, 2024):
update ollama to version 0.1.42 , then ok
@Fau57 commented on GitHub (Jun 10, 2024):
I was using LM studio and just had to update btw
@ligson commented on GitHub (Jun 12, 2024):
time=2024-06-12T17:45:14.644+08:00 level=INFO source=sched.go:338 msg="loaded runners" count=1
time=2024-06-12T17:45:14.644+08:00 level=INFO source=server.go:529 msg="waiting for llama runner to start responding"
time=2024-06-12T17:45:14.644+08:00 level=INFO source=server.go:567 msg="waiting for server to become available" status="llm server error"
INFO [wmain] build info | build=2770 commit="952d03d" tid="32236" timestamp=1718185514
INFO [wmain] system info | n_threads=10 n_threads_batch=-1 system_info="AVX = 1 | AVX_VNNI = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 0 | NEON = 0 | ARM_FMA = 0 | F16C = 0 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 0 | SSSE3 = 0 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 | " tid="32236" timestamp=1718185514 total_threads=20
INFO [wmain] HTTP server listening | hostname="127.0.0.1" n_threads_http="19" port="57166" tid="32236" timestamp=1718185514
llama_model_loader: loaded meta data with 21 key-value pairs and 338 tensors from E:\chatglm\ollama\models\blobs\sha256-405b56374e02b21122ae1469db646be0617c02928fd78e246723ebbb98dbca3e (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = qwen2
llama_model_loader: - kv 1: general.name str = Qwen2-1.5B-Instruct
llama_model_loader: - kv 2: qwen2.block_count u32 = 28
llama_model_loader: - kv 3: qwen2.context_length u32 = 32768
llama_model_loader: - kv 4: qwen2.embedding_length u32 = 1536
llama_model_loader: - kv 5: qwen2.feed_forward_length u32 = 8960
llama_model_loader: - kv 6: qwen2.attention.head_count u32 = 12
llama_model_loader: - kv 7: qwen2.attention.head_count_kv u32 = 2
llama_model_loader: - kv 8: qwen2.rope.freq_base f32 = 1000000.000000
llama_model_loader: - kv 9: qwen2.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 10: general.file_type u32 = 2
llama_model_loader: - kv 11: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 12: tokenizer.ggml.pre str = qwen2
llama_model_loader: - kv 13: tokenizer.ggml.tokens arr[str,151936] = ["!", """, "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 14: tokenizer.ggml.token_type arr[i32,151936] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 15: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv 16: tokenizer.ggml.eos_token_id u32 = 151645
llama_model_loader: - kv 17: tokenizer.ggml.padding_token_id u32 = 151643
llama_model_loader: - kv 18: tokenizer.ggml.bos_token_id u32 = 151643
llama_model_loader: - kv 19: tokenizer.chat_template str = {% for message in messages %}{% if lo...
llama_model_loader: - kv 20: general.quantization_version u32 = 2
llama_model_loader: - type f32: 141 tensors
llama_model_loader: - type q4_0: 196 tensors
llama_model_loader: - type q6_K: 1 tensors
llama_model_load: error loading model: error loading model vocabulary: unknown pre-tokenizer type: 'qwen2'
llama_load_model_from_file: exception loading model
time=2024-06-12T17:45:15.283+08:00 level=ERROR source=sched.go:344 msg="error loading llama server" error="llama runner process has terminated: exit status 0xc0000409 "
ollama version:
ollama version is 0.1.43
windows 11
@QiuZiXian commented on GitHub (Jun 18, 2024):
升级ollama
@jmorganca commented on GitHub (Jun 24, 2024):
Hi folks sorry about the errors. Qwen 2 requires a newer version of Ollama: https://ollama.com/download make sure to update and let me know if this issue persists
@sorenchiron commented on GitHub (Jul 6, 2024):
This solution works for me. Similar error voilates LM-Studio's pipeline too.
For those who cloned only one commit:
@Rodert commented on GitHub (Jul 8, 2024):
run llama3 8b How much configuration is required。 Is 4g memory enough?
运行llama3 8b需要多少配置。4g内存够吗?
我得到一个错误:
ollama Error: llama runner process has terminated: signal: aborted (core dum.@hemangjoshi37a commented on GitHub (Jul 15, 2024):
I am running it using docker container . how am i suppose to run
git hard resetcommand. i dont have access to these as i am running in the cloud docker container. how to resolve this in my situation ?