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mwitiderrick_open_llama_3b_code_instruct_0.1-GGUF
File size: 11,168 Bytes 
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---
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
---

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## 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).

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## 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'
```