| --- |
| language: |
| - en |
| license: apache-2.0 |
| library_name: transformers |
| tags: |
| - transformers |
| - TensorBlock |
| - GGUF |
| datasets: |
| - mwitiderrick/AlpacaCode |
| base_model: mwitiderrick/open_llama_3b_code_instruct_0.1 |
| inference: true |
| model_type: llama |
| prompt_template: '### Instruction:\n |
| |
| {prompt} |
| |
| ### Response: |
| |
| ' |
| created_by: mwitiderrick |
| pipeline_tag: text-generation |
| model-index: |
| - name: mwitiderrick/open_llama_3b_instruct_v_0.2 |
| results: |
| - task: |
| type: text-generation |
| dataset: |
| name: hellaswag |
| type: hellaswag |
| metrics: |
| - type: hellaswag (0-Shot) |
| value: 0.6581 |
| name: hellaswag(0-Shot) |
| - task: |
| type: text-generation |
| dataset: |
| name: winogrande |
| type: winogrande |
| metrics: |
| - type: winogrande (0-Shot) |
| value: 0.6267 |
| name: winogrande(0-Shot) |
| - task: |
| type: text-generation |
| dataset: |
| name: arc_challenge |
| type: arc_challenge |
| metrics: |
| - type: arc_challenge (0-Shot) |
| value: 0.3712 |
| name: arc_challenge(0-Shot) |
| source: |
| url: https://huggingface.co/mwitiderrick/open_llama_3b_instruct_v_0.2 |
| name: open_llama_3b_instruct_v_0.2 model card |
| - task: |
| type: text-generation |
| name: Text Generation |
| dataset: |
| name: AI2 Reasoning Challenge (25-Shot) |
| type: ai2_arc |
| config: ARC-Challenge |
| split: test |
| args: |
| num_few_shot: 25 |
| metrics: |
| - type: acc_norm |
| value: 41.21 |
| name: normalized accuracy |
| source: |
| url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mwitiderrick/open_llama_3b_code_instruct_0.1 |
| name: Open LLM Leaderboard |
| - task: |
| type: text-generation |
| name: Text Generation |
| dataset: |
| name: HellaSwag (10-Shot) |
| type: hellaswag |
| split: validation |
| args: |
| num_few_shot: 10 |
| metrics: |
| - type: acc_norm |
| value: 66.96 |
| name: normalized accuracy |
| source: |
| url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mwitiderrick/open_llama_3b_code_instruct_0.1 |
| name: Open LLM Leaderboard |
| - task: |
| type: text-generation |
| name: Text Generation |
| dataset: |
| name: MMLU (5-Shot) |
| type: cais/mmlu |
| config: all |
| split: test |
| args: |
| num_few_shot: 5 |
| metrics: |
| - type: acc |
| value: 27.82 |
| name: accuracy |
| source: |
| url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mwitiderrick/open_llama_3b_code_instruct_0.1 |
| name: Open LLM Leaderboard |
| - task: |
| type: text-generation |
| name: Text Generation |
| dataset: |
| name: TruthfulQA (0-shot) |
| type: truthful_qa |
| config: multiple_choice |
| split: validation |
| args: |
| num_few_shot: 0 |
| metrics: |
| - type: mc2 |
| value: 35.01 |
| source: |
| url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mwitiderrick/open_llama_3b_code_instruct_0.1 |
| name: Open LLM Leaderboard |
| - task: |
| type: text-generation |
| name: Text Generation |
| dataset: |
| name: Winogrande (5-shot) |
| type: winogrande |
| config: winogrande_xl |
| split: validation |
| args: |
| num_few_shot: 5 |
| metrics: |
| - type: acc |
| value: 65.43 |
| name: accuracy |
| source: |
| url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mwitiderrick/open_llama_3b_code_instruct_0.1 |
| name: Open LLM Leaderboard |
| - task: |
| type: text-generation |
| name: Text Generation |
| dataset: |
| name: GSM8k (5-shot) |
| type: gsm8k |
| config: main |
| split: test |
| args: |
| num_few_shot: 5 |
| metrics: |
| - type: acc |
| value: 1.9 |
| name: accuracy |
| source: |
| url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mwitiderrick/open_llama_3b_code_instruct_0.1 |
| name: Open LLM Leaderboard |
| --- |
| |
| <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) |
|
|
|
|
| ## mwitiderrick/open_llama_3b_code_instruct_0.1 - GGUF |
| |
| This repo contains GGUF format model files for [mwitiderrick/open_llama_3b_code_instruct_0.1](https://huggingface.co/mwitiderrick/open_llama_3b_code_instruct_0.1). |
| |
| The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b5165](https://github.com/ggml-org/llama.cpp/commit/1d735c0b4fa0551c51c2f4ac888dd9a01f447985). |
| |
| ## 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; |
| ">π Try it now! π</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; |
| ">π See what we built π</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; |
| ">π See what we built π</a> |
| </th> |
| </tr> |
| </table> |
| |
| ## Prompt template |
| |
| ``` |
| Unable to determine prompt format automatically. Please check the original model repository for the correct prompt format. |
| ``` |
| |
| ## Model file specification |
| |
| | Filename | Quant type | File Size | Description | |
| | -------- | ---------- | --------- | ----------- | |
| | [open_llama_3b_code_instruct_0.1-Q2_K.gguf](https://huggingface.co/tensorblock/mwitiderrick_open_llama_3b_code_instruct_0.1-GGUF/blob/main/open_llama_3b_code_instruct_0.1-Q2_K.gguf) | Q2_K | 1.980 GB | smallest, significant quality loss - not recommended for most purposes | |
| | [open_llama_3b_code_instruct_0.1-Q3_K_S.gguf](https://huggingface.co/tensorblock/mwitiderrick_open_llama_3b_code_instruct_0.1-GGUF/blob/main/open_llama_3b_code_instruct_0.1-Q3_K_S.gguf) | Q3_K_S | 1.980 GB | very small, high quality loss | |
| | [open_llama_3b_code_instruct_0.1-Q3_K_M.gguf](https://huggingface.co/tensorblock/mwitiderrick_open_llama_3b_code_instruct_0.1-GGUF/blob/main/open_llama_3b_code_instruct_0.1-Q3_K_M.gguf) | Q3_K_M | 2.139 GB | very small, high quality loss | |
| | [open_llama_3b_code_instruct_0.1-Q3_K_L.gguf](https://huggingface.co/tensorblock/mwitiderrick_open_llama_3b_code_instruct_0.1-GGUF/blob/main/open_llama_3b_code_instruct_0.1-Q3_K_L.gguf) | Q3_K_L | 2.215 GB | small, substantial quality loss | |
| | [open_llama_3b_code_instruct_0.1-Q4_0.gguf](https://huggingface.co/tensorblock/mwitiderrick_open_llama_3b_code_instruct_0.1-GGUF/blob/main/open_llama_3b_code_instruct_0.1-Q4_0.gguf) | Q4_0 | 1.980 GB | legacy; small, very high quality loss - prefer using Q3_K_M | |
| | [open_llama_3b_code_instruct_0.1-Q4_K_S.gguf](https://huggingface.co/tensorblock/mwitiderrick_open_llama_3b_code_instruct_0.1-GGUF/blob/main/open_llama_3b_code_instruct_0.1-Q4_K_S.gguf) | Q4_K_S | 2.403 GB | small, greater quality loss | |
| | [open_llama_3b_code_instruct_0.1-Q4_K_M.gguf](https://huggingface.co/tensorblock/mwitiderrick_open_llama_3b_code_instruct_0.1-GGUF/blob/main/open_llama_3b_code_instruct_0.1-Q4_K_M.gguf) | Q4_K_M | 2.580 GB | medium, balanced quality - recommended | |
| | [open_llama_3b_code_instruct_0.1-Q5_0.gguf](https://huggingface.co/tensorblock/mwitiderrick_open_llama_3b_code_instruct_0.1-GGUF/blob/main/open_llama_3b_code_instruct_0.1-Q5_0.gguf) | Q5_0 | 2.395 GB | legacy; medium, balanced quality - prefer using Q4_K_M | |
| | [open_llama_3b_code_instruct_0.1-Q5_K_S.gguf](https://huggingface.co/tensorblock/mwitiderrick_open_llama_3b_code_instruct_0.1-GGUF/blob/main/open_llama_3b_code_instruct_0.1-Q5_K_S.gguf) | Q5_K_S | 2.603 GB | large, low quality loss - recommended | |
| | [open_llama_3b_code_instruct_0.1-Q5_K_M.gguf](https://huggingface.co/tensorblock/mwitiderrick_open_llama_3b_code_instruct_0.1-GGUF/blob/main/open_llama_3b_code_instruct_0.1-Q5_K_M.gguf) | Q5_K_M | 2.757 GB | large, very low quality loss - recommended | |
| | [open_llama_3b_code_instruct_0.1-Q6_K.gguf](https://huggingface.co/tensorblock/mwitiderrick_open_llama_3b_code_instruct_0.1-GGUF/blob/main/open_llama_3b_code_instruct_0.1-Q6_K.gguf) | Q6_K | 3.642 GB | very large, extremely low quality loss | |
| | [open_llama_3b_code_instruct_0.1-Q8_0.gguf](https://huggingface.co/tensorblock/mwitiderrick_open_llama_3b_code_instruct_0.1-GGUF/blob/main/open_llama_3b_code_instruct_0.1-Q8_0.gguf) | Q8_0 | 3.642 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/mwitiderrick_open_llama_3b_code_instruct_0.1-GGUF --include "open_llama_3b_code_instruct_0.1-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/mwitiderrick_open_llama_3b_code_instruct_0.1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf' |
| ``` |
|
|