| | --- |
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| | license: cc-by-nc-4.0 |
| | library_name: transformers |
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| | I agree to use this model for non-commercial use ONLY: checkbox |
| | base_model: CohereForAI/c4ai-command-r-v01 |
| | tags: |
| | - TensorBlock |
| | - GGUF |
| | --- |
| | |
| | <div style="width: auto; margin-left: auto; margin-right: auto"> |
| | <img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;"> |
| | </div> |
| |
|
| | [](https://tensorblock.co) |
| | [](https://twitter.com/tensorblock_aoi) |
| | [](https://discord.gg/Ej5NmeHFf2) |
| | [](https://github.com/TensorBlock) |
| | [](https://t.me/TensorBlock) |
| |
|
| |
|
| | ## CohereForAI/c4ai-command-r-v01 - GGUF |
| |
|
| | This repo contains GGUF format model files for [CohereForAI/c4ai-command-r-v01](https://huggingface.co/CohereForAI/c4ai-command-r-v01). |
| |
|
| | The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d). |
| |
|
| | ## Our projects |
| | <table border="1" cellspacing="0" cellpadding="10"> |
| | <tr> |
| | <th colspan="2" style="font-size: 25px;">Forge</th> |
| | </tr> |
| | <tr> |
| | <th colspan="2"> |
| | <img src="https://imgur.com/faI5UKh.jpeg" alt="Forge Project" width="900"/> |
| | </th> |
| | </tr> |
| | <tr> |
| | <th colspan="2">An OpenAI-compatible multi-provider routing layer.</th> |
| | </tr> |
| | <tr> |
| | <th colspan="2"> |
| | <a href="https://github.com/TensorBlock/forge" target="_blank" style=" |
| | display: inline-block; |
| | padding: 8px 16px; |
| | background-color: #FF7F50; |
| | color: white; |
| | text-decoration: none; |
| | border-radius: 6px; |
| | font-weight: bold; |
| | font-family: sans-serif; |
| | ">🚀 Try it now! 🚀</a> |
| | </th> |
| | </tr> |
| | |
| | <tr> |
| | <th style="font-size: 25px;">Awesome MCP Servers</th> |
| | <th style="font-size: 25px;">TensorBlock Studio</th> |
| | </tr> |
| | <tr> |
| | <th><img src="https://imgur.com/2Xov7B7.jpeg" alt="MCP Servers" width="450"/></th> |
| | <th><img src="https://imgur.com/pJcmF5u.jpeg" alt="Studio" width="450"/></th> |
| | </tr> |
| | <tr> |
| | <th>A comprehensive collection of Model Context Protocol (MCP) servers.</th> |
| | <th>A lightweight, open, and extensible multi-LLM interaction studio.</th> |
| | </tr> |
| | <tr> |
| | <th> |
| | <a href="https://github.com/TensorBlock/awesome-mcp-servers" target="_blank" style=" |
| | display: inline-block; |
| | padding: 8px 16px; |
| | background-color: #FF7F50; |
| | color: white; |
| | text-decoration: none; |
| | border-radius: 6px; |
| | font-weight: bold; |
| | font-family: sans-serif; |
| | ">👀 See what we built 👀</a> |
| | </th> |
| | <th> |
| | <a href="https://github.com/TensorBlock/TensorBlock-Studio" target="_blank" style=" |
| | display: inline-block; |
| | padding: 8px 16px; |
| | background-color: #FF7F50; |
| | color: white; |
| | text-decoration: none; |
| | border-radius: 6px; |
| | font-weight: bold; |
| | font-family: sans-serif; |
| | ">👀 See what we built 👀</a> |
| | </th> |
| | </tr> |
| | </table> |
| | ## Prompt template |
| | |
| | ``` |
| | <BOS_TOKEN><|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>{system_prompt}<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|USER_TOKEN|>{prompt}<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|> |
| | ``` |
| |
|
| | ## Model file specification |
| |
|
| | | Filename | Quant type | File Size | Description | |
| | | -------- | ---------- | --------- | ----------- | |
| | | [c4ai-command-r-v01-Q2_K.gguf](https://huggingface.co/tensorblock/c4ai-command-r-v01-GGUF/blob/main/c4ai-command-r-v01-Q2_K.gguf) | Q2_K | 13.817 GB | smallest, significant quality loss - not recommended for most purposes | |
| | | [c4ai-command-r-v01-Q3_K_S.gguf](https://huggingface.co/tensorblock/c4ai-command-r-v01-GGUF/blob/main/c4ai-command-r-v01-Q3_K_S.gguf) | Q3_K_S | 15.862 GB | very small, high quality loss | |
| | | [c4ai-command-r-v01-Q3_K_M.gguf](https://huggingface.co/tensorblock/c4ai-command-r-v01-GGUF/blob/main/c4ai-command-r-v01-Q3_K_M.gguf) | Q3_K_M | 17.618 GB | very small, high quality loss | |
| | | [c4ai-command-r-v01-Q3_K_L.gguf](https://huggingface.co/tensorblock/c4ai-command-r-v01-GGUF/blob/main/c4ai-command-r-v01-Q3_K_L.gguf) | Q3_K_L | 19.149 GB | small, substantial quality loss | |
| | | [c4ai-command-r-v01-Q4_0.gguf](https://huggingface.co/tensorblock/c4ai-command-r-v01-GGUF/blob/main/c4ai-command-r-v01-Q4_0.gguf) | Q4_0 | 20.229 GB | legacy; small, very high quality loss - prefer using Q3_K_M | |
| | | [c4ai-command-r-v01-Q4_K_S.gguf](https://huggingface.co/tensorblock/c4ai-command-r-v01-GGUF/blob/main/c4ai-command-r-v01-Q4_K_S.gguf) | Q4_K_S | 20.378 GB | small, greater quality loss | |
| | | [c4ai-command-r-v01-Q4_K_M.gguf](https://huggingface.co/tensorblock/c4ai-command-r-v01-GGUF/blob/main/c4ai-command-r-v01-Q4_K_M.gguf) | Q4_K_M | 21.527 GB | medium, balanced quality - recommended | |
| | | [c4ai-command-r-v01-Q5_0.gguf](https://huggingface.co/tensorblock/c4ai-command-r-v01-GGUF/blob/main/c4ai-command-r-v01-Q5_0.gguf) | Q5_0 | 24.340 GB | legacy; medium, balanced quality - prefer using Q4_K_M | |
| | | [c4ai-command-r-v01-Q5_K_S.gguf](https://huggingface.co/tensorblock/c4ai-command-r-v01-GGUF/blob/main/c4ai-command-r-v01-Q5_K_S.gguf) | Q5_K_S | 24.340 GB | large, low quality loss - recommended | |
| | | [c4ai-command-r-v01-Q5_K_M.gguf](https://huggingface.co/tensorblock/c4ai-command-r-v01-GGUF/blob/main/c4ai-command-r-v01-Q5_K_M.gguf) | Q5_K_M | 25.008 GB | large, very low quality loss - recommended | |
| | | [c4ai-command-r-v01-Q6_K.gguf](https://huggingface.co/tensorblock/c4ai-command-r-v01-GGUF/blob/main/c4ai-command-r-v01-Q6_K.gguf) | Q6_K | 28.707 GB | very large, extremely low quality loss | |
| | | [c4ai-command-r-v01-Q8_0.gguf](https://huggingface.co/tensorblock/c4ai-command-r-v01-GGUF/blob/main/c4ai-command-r-v01-Q8_0.gguf) | Q8_0 | 37.179 GB | very large, extremely low quality loss - not recommended | |
| | |
| | |
| | ## Downloading instruction |
| | |
| | ### Command line |
| | |
| | Firstly, install Huggingface Client |
| | |
| | ```shell |
| | pip install -U "huggingface_hub[cli]" |
| | ``` |
| | |
| | Then, downoad the individual model file the a local directory |
| | |
| | ```shell |
| | huggingface-cli download tensorblock/c4ai-command-r-v01-GGUF --include "c4ai-command-r-v01-Q2_K.gguf" --local-dir MY_LOCAL_DIR |
| | ``` |
| | |
| | If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try: |
| | |
| | ```shell |
| | huggingface-cli download tensorblock/c4ai-command-r-v01-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf' |
| | ``` |
| | |
