[GH-ISSUE #2965] Is it possible to support more embedding models in the future? #1821

New Issue

GiteaMirror · 2026-04-12T11:52:45-05:00

GiteaMirror commented

2026-04-12 11:52:45 -05:00

Originally created by @wwjCMP on GitHub (Mar 7, 2024).
Original GitHub issue: https://github.com/ollama/ollama/issues/2965

The nomic-embed-text is great, but it does not support Chinese.

Originally created by @wwjCMP on GitHub (Mar 7, 2024). Original GitHub issue: https://github.com/ollama/ollama/issues/2965 The nomic-embed-text is great, but it does not support Chinese.

GiteaMirror added the model label 2026-04-12 11:52:45 -05:00

GiteaMirror closed this issue

2026-04-12 11:52:46 -05:00

GiteaMirror commented

2026-04-12 11:52:47 -05:00

@jackleeforce commented on GitHub (Mar 7, 2024):

jina-embeddings-v2-base-zh is good,but i have no idea for how to run it with ollama. i'm trying for this: https://github.com/ollama/ollama/issues/327

@jackleeforce commented on GitHub (Mar 7, 2024): jina-embeddings-v2-base-zh is good,but i have no idea for how to run it with ollama. i'm trying for this: https://github.com/ollama/ollama/issues/327

GiteaMirror commented

2026-04-12 11:52:47 -05:00

@jackleeforce commented on GitHub (Mar 7, 2024):

ok,now i run a customized embedding model Dmeta-embedding-zh successfully with ollama, since ollama using llama.cpp as inference, and it support BERT which is architecture of most of embedding model, following is steps:

Coverting hugging-face model into GGUF file

1. git clone https://github.com/ggerganov/llama.cpp.git
2. cd llama.cpp
3. downloading embedding model https://huggingface.co/DMetaSoul/Dmeta-embedding-zh into folder llama.cpp/models
4. python3.11 convert-hf-to-gguf.py --outtype f32 ./models/Dmeta-embedding-zh --outfile ./models/Dmeta-embedding-zh/Dmeta-embedding-zh.gguf
5. Dmeta-embedding-zh.gguf is the only file we needed for next step.

Add customize model into ollama
- According Tutorial in import-from-gguf
Enjoy it !

@jackleeforce commented on GitHub (Mar 7, 2024): ok,now i run a customized embedding model [Dmeta-embedding-zh](https://huggingface.co/DMetaSoul/Dmeta-embedding-zh) successfully with [ollama](https://github.com/ollama/ollama), since [ollama](https://github.com/ollama/ollama) using [llama.cpp](https://github.com/ggerganov/llama.cpp) as inference, and it support BERT which is architecture of most of embedding model, following is steps: - Coverting hugging-face model into GGUF file ``` 1. git clone https://github.com/ggerganov/llama.cpp.git 2. cd llama.cpp 3. downloading embedding model https://huggingface.co/DMetaSoul/Dmeta-embedding-zh into folder llama.cpp/models 4. python3.11 convert-hf-to-gguf.py --outtype f32 ./models/Dmeta-embedding-zh --outfile ./models/Dmeta-embedding-zh/Dmeta-embedding-zh.gguf 5. Dmeta-embedding-zh.gguf is the only file we needed for next step. ``` - Add customize model into [ollama](https://github.com/ollama/ollama) - According Tutorial in [import-from-gguf](https://github.com/ollama/ollama?tab=readme-ov-file#import-from-gguf) - Enjoy it !

GiteaMirror commented

2026-04-12 11:52:48 -05:00

@wwjCMP commented on GitHub (Mar 7, 2024):

ok,now i run a customized embedding model Dmeta-embedding-zh successfully with ollama, since ollama using llama.cpp as inference, and it support BERT which is architecture of most of embedding model, following is steps:

Coverting hugging-face model into GGUF file
1. git clone https://github.com/ggerganov/llama.cpp.git
2. cd llama.cpp
3. downloading embedding model https://huggingface.co/DMetaSoul/Dmeta-embedding-zh into folder llama.cpp/models
4. python3.11 convert-hf-to-gguf.py --outtype f32 ./models/Dmeta-embedding-zh --outfile ./models/Dmeta-embedding-zh/Dmeta-embedding-zh.gguf
5. Dmeta-embedding-zh.gguf is the only file we needed for next step.
Add customize model into ollama

According Tutorial in import-from-gguf

Enjoy it !

I have an unexpected problem here

@wwjCMP commented on GitHub (Mar 7, 2024): > ok,now i run a customized embedding model [Dmeta-embedding-zh](https://huggingface.co/DMetaSoul/Dmeta-embedding-zh) successfully with [ollama](https://github.com/ollama/ollama), since [ollama](https://github.com/ollama/ollama) using [llama.cpp](https://github.com/ggerganov/llama.cpp) as inference, and it support BERT which is architecture of most of embedding model, following is steps: > > * Coverting hugging-face model into GGUF file > > ``` > 1. git clone https://github.com/ggerganov/llama.cpp.git > 2. cd llama.cpp > 3. downloading embedding model https://huggingface.co/DMetaSoul/Dmeta-embedding-zh into folder llama.cpp/models > 4. python3.11 convert-hf-to-gguf.py --outtype f32 ./models/Dmeta-embedding-zh --outfile ./models/Dmeta-embedding-zh/Dmeta-embedding-zh.gguf > 5. Dmeta-embedding-zh.gguf is the only file we needed for next step. > ``` > > * Add customize model into [ollama](https://github.com/ollama/ollama) > > * According Tutorial in [import-from-gguf](https://github.com/ollama/ollama?tab=readme-ov-file#import-from-gguf) > * Enjoy it ! ![Snipaste_2024-03-07_18-31-41](https://github.com/ollama/ollama/assets/32979859/1cd74cc5-51be-4eaa-9aae-020ea2636c55) I have an unexpected problem here

GiteaMirror commented

2026-04-12 11:52:49 -05:00

@wwjCMP commented on GitHub (Mar 7, 2024):

ok,now i run a customized embedding model Dmeta-embedding-zh successfully with ollama, since ollama using llama.cpp as inference, and it support BERT which is architecture of most of embedding model, following is steps:

Coverting hugging-face model into GGUF file
1. git clone https://github.com/ggerganov/llama.cpp.git
2. cd llama.cpp
3. downloading embedding model https://huggingface.co/DMetaSoul/Dmeta-embedding-zh into folder llama.cpp/models
4. python3.11 convert-hf-to-gguf.py --outtype f32 ./models/Dmeta-embedding-zh --outfile ./models/Dmeta-embedding-zh/Dmeta-embedding-zh.gguf
5. Dmeta-embedding-zh.gguf is the only file we needed for next step.
Add customize model into ollama

According Tutorial in import-from-gguf

Enjoy it !

Can the model you converted be used normally?

@wwjCMP commented on GitHub (Mar 7, 2024): > ok,now i run a customized embedding model [Dmeta-embedding-zh](https://huggingface.co/DMetaSoul/Dmeta-embedding-zh) successfully with [ollama](https://github.com/ollama/ollama), since [ollama](https://github.com/ollama/ollama) using [llama.cpp](https://github.com/ggerganov/llama.cpp) as inference, and it support BERT which is architecture of most of embedding model, following is steps: > > * Coverting hugging-face model into GGUF file > > ``` > 1. git clone https://github.com/ggerganov/llama.cpp.git > 2. cd llama.cpp > 3. downloading embedding model https://huggingface.co/DMetaSoul/Dmeta-embedding-zh into folder llama.cpp/models > 4. python3.11 convert-hf-to-gguf.py --outtype f32 ./models/Dmeta-embedding-zh --outfile ./models/Dmeta-embedding-zh/Dmeta-embedding-zh.gguf > 5. Dmeta-embedding-zh.gguf is the only file we needed for next step. > ``` > > * Add customize model into [ollama](https://github.com/ollama/ollama) > > * According Tutorial in [import-from-gguf](https://github.com/ollama/ollama?tab=readme-ov-file#import-from-gguf) > * Enjoy it ! Can the model you converted be used normally?

GiteaMirror commented

2026-04-12 11:52:50 -05:00

@jackleeforce commented on GitHub (Mar 8, 2024):

ok,now i run a customized embedding model Dmeta-embedding-zh successfully with ollama, since ollama using llama.cpp as inference, and it support BERT which is architecture of most of embedding model, following is steps:

Coverting hugging-face model into GGUF file
1. git clone https://github.com/ggerganov/llama.cpp.git
2. cd llama.cpp
3. downloading embedding model https://huggingface.co/DMetaSoul/Dmeta-embedding-zh into folder llama.cpp/models
4. python3.11 convert-hf-to-gguf.py --outtype f32 ./models/Dmeta-embedding-zh --outfile ./models/Dmeta-embedding-zh/Dmeta-embedding-zh.gguf
5. Dmeta-embedding-zh.gguf is the only file we needed for next step.
Add customize model into ollama

According Tutorial in import-from-gguf

Enjoy it !
I have an unexpected problem here

after you create the example from Modelfile, no need to using ollama pull , ollama pull is used pull model from official repository, actually after ollama create example -f Modelfile, then the model example is in your local environment, just using 'ollama run example':

@jackleeforce commented on GitHub (Mar 8, 2024): > > ok,now i run a customized embedding model [Dmeta-embedding-zh](https://huggingface.co/DMetaSoul/Dmeta-embedding-zh) successfully with [ollama](https://github.com/ollama/ollama), since [ollama](https://github.com/ollama/ollama) using [llama.cpp](https://github.com/ggerganov/llama.cpp) as inference, and it support BERT which is architecture of most of embedding model, following is steps: > > > > * Coverting hugging-face model into GGUF file > > > > ``` > > 1. git clone https://github.com/ggerganov/llama.cpp.git > > 2. cd llama.cpp > > 3. downloading embedding model https://huggingface.co/DMetaSoul/Dmeta-embedding-zh into folder llama.cpp/models > > 4. python3.11 convert-hf-to-gguf.py --outtype f32 ./models/Dmeta-embedding-zh --outfile ./models/Dmeta-embedding-zh/Dmeta-embedding-zh.gguf > > 5. Dmeta-embedding-zh.gguf is the only file we needed for next step. > > ``` > > > > > > > > > > > > > > > > > > > > > > > > > > * Add customize model into [ollama](https://github.com/ollama/ollama) > > > > * According Tutorial in [import-from-gguf](https://github.com/ollama/ollama?tab=readme-ov-file#import-from-gguf) > > * Enjoy it ! > > ![Snipaste_2024-03-07_18-31-41](https://private-user-images.githubusercontent.com/32979859/310844442-1cd74cc5-51be-4eaa-9aae-020ea2636c55.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.lXdusQXgP95R-_iJRq95hz-HHSs_kuA-wAtKkX0Fgfo) I have an unexpected problem here after you create the `example` from `Modelfile`, no need to using `ollama pull` , `ollama pull` is used pull model from official repository, actually after `ollama create example -f Modelfile`, then the model `example` is in your local environment, just using 'ollama run example': <img width="1045" alt="image" src="https://github.com/ollama/ollama/assets/4516554/54029a80-c63f-4206-a0a4-d7d84eee429e">

GiteaMirror commented

2026-04-12 11:52:51 -05:00

@jackleeforce commented on GitHub (Mar 8, 2024):

ok,now i run a customized embedding model Dmeta-embedding-zh successfully with ollama, since ollama using llama.cpp as inference, and it support BERT which is architecture of most of embedding model, following is steps:

Coverting hugging-face model into GGUF file
1. git clone https://github.com/ggerganov/llama.cpp.git
2. cd llama.cpp
3. downloading embedding model https://huggingface.co/DMetaSoul/Dmeta-embedding-zh into folder llama.cpp/models
4. python3.11 convert-hf-to-gguf.py --outtype f32 ./models/Dmeta-embedding-zh --outfile ./models/Dmeta-embedding-zh/Dmeta-embedding-zh.gguf
5. Dmeta-embedding-zh.gguf is the only file we needed for next step.
Add customize model into ollama

According Tutorial in import-from-gguf

Enjoy it !
Can the model you converted be used normally?

yes, i integrated it into dify, work perfect~

@jackleeforce commented on GitHub (Mar 8, 2024): > > ok,now i run a customized embedding model [Dmeta-embedding-zh](https://huggingface.co/DMetaSoul/Dmeta-embedding-zh) successfully with [ollama](https://github.com/ollama/ollama), since [ollama](https://github.com/ollama/ollama) using [llama.cpp](https://github.com/ggerganov/llama.cpp) as inference, and it support BERT which is architecture of most of embedding model, following is steps: > > > > * Coverting hugging-face model into GGUF file > > > > ``` > > 1. git clone https://github.com/ggerganov/llama.cpp.git > > 2. cd llama.cpp > > 3. downloading embedding model https://huggingface.co/DMetaSoul/Dmeta-embedding-zh into folder llama.cpp/models > > 4. python3.11 convert-hf-to-gguf.py --outtype f32 ./models/Dmeta-embedding-zh --outfile ./models/Dmeta-embedding-zh/Dmeta-embedding-zh.gguf > > 5. Dmeta-embedding-zh.gguf is the only file we needed for next step. > > ``` > > > > > > > > > > > > > > > > > > > > > > > > > > * Add customize model into [ollama](https://github.com/ollama/ollama) > > > > * According Tutorial in [import-from-gguf](https://github.com/ollama/ollama?tab=readme-ov-file#import-from-gguf) > > * Enjoy it ! > > Can the model you converted be used normally? yes, i integrated it into [dify](https://github.com/langgenius/dify), work perfect~

GiteaMirror commented

2026-04-12 11:52:52 -05:00

@wwjCMP commented on GitHub (Mar 8, 2024):

好的，现在我用ollama成功运行了一个定制的嵌入模型Dmeta-embedding-zh，因为ollama使用llama.cpp作为推理，并且它支持 BERT，这是大多数嵌入模型的架构，以下是步骤：

将拥抱脸模型转换为GGUF文件
1. git clone https://github.com/ggerganov/llama.cpp.git
2. cd llama.cpp
3. downloading embedding model https://huggingface.co/DMetaSoul/Dmeta-embedding-zh into folder llama.cpp/models
4. python3.11 convert-hf-to-gguf.py --outtype f32 ./models/Dmeta-embedding-zh --outfile ./models/Dmeta-embedding-zh/Dmeta-embedding-zh.gguf
5. Dmeta-embedding-zh.gguf is the only file we needed for next step.
将自定义模型添加到ollama中

根据import-from-gguf中的教程

好好享受！
我这里有一个意想不到的问题
创建examplefrom后Modelfile，无需使用ollama pull，ollama pull使用从官方存储库拉取模型，实际上在创建之后ollama create example -f Modelfile，模型example就在您的本地环境中，只需使用“ollama run example”：

At the beginning, I also used the ollama run command, but it gave the following error
Error: embedding models do not support chat

@wwjCMP commented on GitHub (Mar 8, 2024): > > > 好的，现在我用[ollama](https://github.com/ollama/ollama)成功运行了一个定制的嵌入模型[Dmeta-embedding-zh](https://huggingface.co/DMetaSoul/Dmeta-embedding-zh)，因为[ollama](https://github.com/ollama/ollama)使用[llama.cpp](https://github.com/ggerganov/llama.cpp)作为推理，并且它支持 BERT，这是大多数嵌入模型的架构，以下是步骤：[](https://github.com/ollama/ollama)[](https://github.com/ollama/ollama)[](https://github.com/ggerganov/llama.cpp) > > > > > > * 将拥抱脸模型转换为GGUF文件 > > > > > > ``` > > > 1. git clone https://github.com/ggerganov/llama.cpp.git > > > 2. cd llama.cpp > > > 3. downloading embedding model https://huggingface.co/DMetaSoul/Dmeta-embedding-zh into folder llama.cpp/models > > > 4. python3.11 convert-hf-to-gguf.py --outtype f32 ./models/Dmeta-embedding-zh --outfile ./models/Dmeta-embedding-zh/Dmeta-embedding-zh.gguf > > > 5. Dmeta-embedding-zh.gguf is the only file we needed for next step. > > > ``` > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > * 将自定义模型添加到[ollama中](https://github.com/ollama/ollama) > > > > > > * [根据import-from-gguf](https://github.com/ollama/ollama?tab=readme-ov-file#import-from-gguf)中的教程[](https://github.com/ollama/ollama?tab=readme-ov-file#import-from-gguf) > > > * 好好享受！ > > > > > > ![Snipaste_2024-03-07_18-31-41](https://private-user-images.githubusercontent.com/32979859/310844442-1cd74cc5-51be-4eaa-9aae-020ea2636c55.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.lXdusQXgP95R-_iJRq95hz-HHSs_kuA-wAtKkX0Fgfo)我这里有一个意想不到的问题 > > 创建`example`from后`Modelfile`，无需使用`ollama pull`，`ollama pull`使用从官方存储库拉取模型，实际上在创建之后`ollama create example -f Modelfile`，模型`example`就在您的本地环境中，只需使用“ollama run example”： > > <img alt="图像" width="1045" src="https://private-user-images.githubusercontent.com/4516554/311083597-54029a80-c63f-4206-a0a4-d7d84eee429e.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.WKfvtyxIL3sFn4u32X8y3ysopCwVbOo9sz9_vvTrSKQ"> At the beginning, I also used the `ollama run` command, but it gave the following error `Error: embedding models do not support chat`

GiteaMirror commented

2026-04-12 11:52:53 -05:00

@wwjCMP commented on GitHub (Mar 8, 2024):

I think I got it

@wwjCMP commented on GitHub (Mar 8, 2024): I think I got it

GiteaMirror referenced this issue

2026-04-12 23:07:48 -05:00

[PR #1819] [MERGED] Support multiple LLM libs; ROCm v5 and v6; Rosetta, AVX, and AVX2 compatible CPU builds #10693

GiteaMirror referenced this issue

2026-04-16 05:12:52 -05:00

[PR #1819] [MERGED] Support multiple LLM libs; ROCm v5 and v6; Rosetta, AVX, and AVX2 compatible CPU builds #15964

GiteaMirror referenced this issue

2026-04-19 15:31:57 -05:00

[PR #1819] [MERGED] Support multiple LLM libs; ROCm v5 and v6; Rosetta, AVX, and AVX2 compatible CPU builds #21233

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2026-04-22 03:24:44 -05:00

[GH-ISSUE #1821] amd64 binary for version 0.1.18 won't work with rocm-6.0.0 #26797

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2026-04-22 21:12:09 -05:00

[PR #1819] [MERGED] Support multiple LLM libs; ROCm v5 and v6; Rosetta, AVX, and AVX2 compatible CPU builds #36566

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2026-04-24 21:44:57 -05:00

[PR #1819] [MERGED] Support multiple LLM libs; ROCm v5 and v6; Rosetta, AVX, and AVX2 compatible CPU builds #41941

GiteaMirror referenced this issue

2026-04-28 04:08:48 -05:00

[GH-ISSUE #1821] amd64 binary for version 0.1.18 won't work with rocm-6.0.0 #47549

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2026-04-29 11:59:19 -05:00

[PR #1819] [MERGED] Support multiple LLM libs; ROCm v5 and v6; Rosetta, AVX, and AVX2 compatible CPU builds #57390

GiteaMirror referenced this issue

2026-05-03 11:39:46 -05:00

[GH-ISSUE #1821] amd64 binary for version 0.1.18 won't work with rocm-6.0.0 #63074

GiteaMirror referenced this issue

2026-05-05 04:36:22 -05:00

[PR #1819] [MERGED] Support multiple LLM libs; ROCm v5 and v6; Rosetta, AVX, and AVX2 compatible CPU builds #72987

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brucemacd/install-server-wait

parth/update-claude-docs

brucemac/start-ap-install

pdevine/mlx-update

pdevine/qwen35_vision

drifkin/api-show-fallback

mintlify/image-generation-1773352582

hoyyeva/server-context-length-local-config

jmorganca/faster-reptition-penalties

jmorganca/convert-nemotron

parth-pi-thinking

pdevine/sampling-penalties

jmorganca/fix-create-quantization-memory

dongchen/resumable_transfer_fix

pdevine/sampling-cache-error

jessegross/mlx-usage

hoyyeva/openclaw-config

hoyyeva/app-html

pdevine/qwen3next

brucemacd/sign-sh-install

brucemacd/tui-update

brucemacd/usage-api

jmorganca/launch-empty

fix-app-dist-embed

mxyng/mlx-compile

mxyng/mlx-quant

mxyng/mlx-glm4.7

mxyng/mlx

brucemacd/simplify-model-picker

jmorganca/qwen3-concurrent

fix-glm-4.7-flash-mla-config

drifkin/qwen3-coder-opening-tag

brucemacd/usage-cli

fix-cuda12-fattn-shmem

ollama-imagegen-docs

parth/fix-multiline-inputs

brucemacd/config-docs

mxyng/model-files

mxyng/simple-execute

fix-imagegen-ollama-models

mxyng/async-upload

jmorganca/lazy-no-dtype-changes

imagegen-auto-detect-create

parth/decrease-concurrent-download-hf

fix-mlx-quantize-init

jmorganca/x-cleanup

usage

imagegen-readme

jmorganca/glm-image

mlx-gpu-cd

jmorganca/imagegen-modelfile

parth/agent-skills

parth/agent-allowlist

parth/signed-in-offline

parth/agents

parth/fix-context-chopping

improve-cloud-flow

parth/add-models-websearch

parth/prompt-renderer-mcp

jmorganca/native-settings

jmorganca/download-stream-hash

jmorganca/client2-rebased

brucemacd/oai-chat-req-multipart

jessegross/multi_chunk_reserve

grace/additional-omit-empty

grace/mistral-3-large

mxyng/tokenizer2

mxyng/tokenizer

jessegross/flash

hoyyeva/windows-nacked-app

mxyng/cleanup-attention

grace/deepseek-parser

hoyyeva/remember-unsent-prompt

parth/add-lfs-pointer-error-conversion

parth/olmo2-test2

hoyyeva/ollama-launchagent-plist

nicole/olmo-model

parth/olmo-test

mxyng/remove-embedded

parth/render-template

jmorganca/intellect-3

parth/remove-prealloc-linter

jmorganca/cmd-eval

nicole/nomic-embed-text-fix

mxyng/lint-2

hoyyeva/add-gemini-3-pro-preview

hoyyeva/load-model-list

mxyng/expand-path

mxyng/environ-2

hoyyeva/deeplink-json-encoding

parth/improve-tool-calling-tests

hoyyeva/conversation

hoyyeva/assistant-edit-response

hoyyeva/thinking

origin/brucemacd/invalid-char-i-err

parth/improve-tool-calling

jmorganca/required-omitempty

grace/qwen3-vl-tests

mxyng/iter-client

parth/docs-readme

nicole/embed-test

pdevine/integration-benchstat

parth/remove-generate-cmd

parth/add-toolcall-id

mxyng/server-tests

jmorganca/glm-4.6

jmorganca/gin-h-compat

drifkin/stable-tool-args

pdevine/qwen3-more-thinking

parth/add-websearch-client

nicole/websearch_local

jmorganca/qwen3-coder-updates

grace/deepseek-v3-migration-tests

mxyng/fix-create

jmorganca/cloud-errors

pdevine/parser-tidy

revert-12233-parth/simplify-entrypoints-runner

parth/enable-so-gpt-oss

brucemacd/qwen3vl

jmorganca/readme-simplify

parth/gpt-oss-structured-outputs

revert-12039-jmorganca/tools-braces

mxyng/embeddings

mxyng/gguf

mxyng/benchmark

mxyng/types-null

parth/move-parsing

mxyng/gemma2

jmorganca/docs

mxyng/16-bit

mxyng/create-stdin

pdevine/authorizedkeys

mxyng/quant

parth/opt-in-error-context-window

brucemacd/cache-models

brucemacd/runner-completion

jmorganca/llama-update-6

brucemacd/benchmark-list

brucemacd/partial-read-caps

parth/deepseek-r1-tools

mxyng/omit-array

parth/tool-prefix-temp

brucemacd/runner-test

jmorganca/qwen25vl

brucemacd/model-forward-test-ext

parth/python-function-parsing

jmorganca/cuda-compression-none

drifkin/num-parallel

drifkin/chat-truncation-fix

jmorganca/sync

parth/python-tools-calling

drifkin/array-head-count

brucemacd/create-no-loop

parth/server-enable-content-stream-with-tools

qwen25omni

mxyng/v3

brucemacd/ropeconfig

jmorganca/silence-tokenizer

parth/sample-so-test

parth/sampling-structured-outputs

brucemacd/doc-go-engine

parth/constrained-sampling-json

jmorganca/mistral-wip

brucemacd/mistral-small-convert

parth/sample-unmarshal-json-for-params

brucemacd/jomorganca/mistral

pdevine/bfloat16

jmorganca/mistral

brucemacd/mistral

pdevine/logging

parth/sample-correctness-fix

parth/sample-fix-sorting

jmorgan/sample-fix-sorting-extras

jmorganca/temp-0-images

brucemacd/parallel-embed-models

brucemacd/shim-grammar

jmorganca/fix-gguf-error

bmizerany/nameswork

jmorganca/faster-releases

bmizerany/validatenames

brucemacd/err-no-vocab

brucemacd/rope-config

brucemacd/err-hint

brucemacd/qwen2_5

brucemacd/logprobs

brucemacd/new_runner_graph_bench

progress-flicker

brucemacd/forward-test

brucemacd/go_qwen2

pdevine/gemma2

jmorganca/add-missing-symlink-eval

mxyng/next-debug

parth/set-context-size-openai

brucemacd/next-bpe-bench

brucemacd/next-bpe-test

brucemacd/new_runner_e2e

brucemacd/new_runner_qwen2

pdevine/convert-cohere2

brucemacd/convert-cli

parth/log-probs

mxyng/next-mlx

mxyng/cmd-history

parth/templating

parth/tokenize-detokenize

brucemacd/check-key-register

bmizerany/grammar

jmorganca/vendor-081b29bd

mxyng/func-checks

jmorganca/fix-null-format

parth/fix-default-to-warn-json

jmorganca/qwen2vl

jmorganca/no-concat

parth/cmd-cleanup-SO

brucemacd/check-key-register-structured-err

parth/openai-stream-usage

parth/fix-referencing-so

stream-tools-stop

jmorganca/degin-1

brucemacd/install-path-clean

brucemacd/push-name-validation

brucemacd/browser-key-register

jmorganca/openai-fix-first-message

jmorganca/fix-proxy

jessegross/sample

parth/disallow-streaming-tools

dhiltgen/remove_submodule

jmorganca/ga

jmorganca/mllama

pdevine/newlines

pdevine/geems-2b

jmorganca/llama-bump

mxyng/modelname-7

mxyng/gin-slog

mxyng/modelname-6

jyan/convert-prog

jyan/quant5

paligemma-support

pdevine/import-docs

jmorganca/openai-context

jyan/paligemma

jyan/p2

jyan/palitest

bmizerany/embedspeedup

jmorganca/llama-vit

brucemacd/allow-ollama

royh/ep-methods

royh/whisper

mxyng/api-models

mxyng/fix-memory

jyan/q4_4/8

jyan/ollama-v

royh/stream-tools

roy-embed-parallel

bmizerany/hrm

revert-5963-revert-5924-mxyng/llama3.1-rope

royh/embed-viz

jyan/local2

jyan/auth

jyan/local

jyan/parse-temp

jmorganca/template-mistral

jyan/reord-g

royh-openai-suffixdocs

royh-imgembed

royh-embed-parallel

jyan/quant4

royh-precision

jyan/progress

pdevine/fix-template

jyan/quant3

pdevine/ggla

mxyng/update-registry-domain

jmorganca/ggml-static

mxyng/create-context

jyan/v0.146

mxyng/layers-from-files

build_dist

bmizerany/noseek

royh-ls

royh-name

timeout

mxyng/server-timestamp

bmizerany/nosillyggufslurps

royh-params

jmorganca/llama-cpp-7c26775

royh-openai-delete

royh-show-rigid

jmorganca/enable-fa

jmorganca/no-error-template

jyan/format

royh-testdelete

bmizerany/fastverify

language_support

pdevine/ps-glitches

brucemacd/tokenize

bruce/iq-quants

bmizerany/filepathwithcoloninhost

mxyng/split-bin

bmizerany/client-registry

jmorganca/if-none-match

native

jmorganca/native

jmorganca/batch-embeddings

jmorganca/initcmake

jmorganca/mm

pdevine/showggmlinfo

modenameenforcealphanum

bmizerany/modenameenforcealphanum

jmorganca/done-reason

jmorganca/llama-cpp-8960fe8

ollama.com

bmizerany/filepathnobuild

bmizerany/types/model/defaultfix

rmdisplaylong

nogogen

bmizerany/x

modelfile-readme

bmizerany/replacecolon

jmorganca/limit

jmorganca/execstack

jmorganca/replace-assets

mxyng/tune-concurrency

jmorganca/testing

whitespace-detection

jmorganca/options

upgrade-all

scratch

cuda-search

mattw/airenamer

mattw/allmodelsonhuggingface

mattw/quantcontext

mattw/whatneedstorun

brucemacd/llama-mem-calc

mattw/faq-context

mattw/communitylinks

mattw/noprune

mattw/python-functioncalling

rename

mxyng/install

pulse

remove-first

editor

mattw/selfqueryingretrieval

cgo

mattw/howtoquant

api

matt/streamingapi

format-config

mxyng/extra-args

shell

update-nous-hermes

cp-model

upload-progress

fix-unknown-model

fix-model-names

delete-fix

insecure-registry

ls

deletemodels

progressbar

readme-updates

license-layers

skip-list

list-models

modelpath

matt/examplemodelfiles

distribution

go-opts

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Reference: github-starred/ollama#1821