File size: 6,280 Bytes

---
license: other
license_name: llama-3
license_link: https://llama.meta.com/llama3/license/
tags:
- text-generation-inference
- transformers
- unsloth
- llama
datasets:
- Replete-AI/code_bagel_hermes-2.5
- Replete-AI/code_bagel
- Replete-AI/OpenHermes-2.5-Uncensored
- teknium/OpenHermes-2.5
- layoric/tiny-codes-alpaca
- glaiveai/glaive-code-assistant-v3
- ajibawa-2023/Code-290k-ShareGPT
- TIGER-Lab/MathInstruct
- chargoddard/commitpack-ft-instruct-rated
- iamturun/code_instructions_120k_alpaca
- ise-uiuc/Magicoder-Evol-Instruct-110K
- cognitivecomputations/dolphin-coder
- nickrosh/Evol-Instruct-Code-80k-v1
- coseal/CodeUltraFeedback_binarized

- glaiveai/glaive-function-calling-v2
- CyberNative/Code_Vulnerability_Security_DPO
- jondurbin/airoboros-2.2
- camel-ai
- lmsys/lmsys-chat-1m
- CollectiveCognition/chats-data-2023-09-22
- CoT-Alpaca-GPT4
- WizardLM/WizardLM_evol_instruct_70k
- WizardLM/WizardLM_evol_instruct_V2_196k
- teknium/GPT4-LLM-Cleaned
- GPTeacher
- OpenGPT
- meta-math/MetaMathQA
- Open-Orca/SlimOrca
- garage-bAInd/Open-Platypus
- anon8231489123/ShareGPT_Vicuna_unfiltered
- Unnatural-Instructions-GPT4
model-index:
- name: Replete-Coder-llama3-8b
  results:
  - task:
      name: HumanEval
      type: text-generation
    dataset:
      type: openai_humaneval
      name: HumanEval
    metrics:
    - name: pass@1
      type: pass@1
      value: 
      verified: false
  - task:
      name: AI2 Reasoning Challenge
      type: text-generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: accuracy
      value: 
      name: normalized accuracy
    source:
      url: https://www.placeholderurl.com
      name: Open LLM Leaderboard
  - task:
      name: Text Generation
      type: text-generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: accuracy
      value: 
      name: normalized accuracy
    source:
      url: https://www.placeholderurl.com
      name: Open LLM Leaderboard
  - task:
      name: Text Generation
      type: text-generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: accuracy
      value: 
      name: accuracy
    source:
      url: https://www.placeholderurl.com
      name: Open LLM Leaderboard
  - task:
      name: Text Generation
      type: text-generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: multiple_choice_accuracy
      value: 
    source:
      url: https://www.placeholderurl.com
      name: Open LLM Leaderboard
  - task:
      name: Text Generation
      type: text-generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: accuracy
      value: 
      name: accuracy
    source:
      url: https://www.placeholderurl.com
      name: Open LLM Leaderboard
  - task:
      name: Text Generation
      type: text-generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: accuracy
      value: 
      name: accuracy
    source:
      url: https://www.placeholderurl.com
      name: Open LLM Leaderboard
quantized_by: bartowski
pipeline_tag: text-generation
---

## Exllama v2 Quantizations of Replete-Coder-Llama3-8B

Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.1.6">turboderp's ExLlamaV2 v0.1.6</a> for quantization.

<b>The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)</b>

Each branch contains an individual bits per weight, with the main one containing only the meaurement.json for further conversions.

Original model: https://huggingface.co/Replete-AI/Replete-Coder-Llama3-8B

## Prompt format

```
### System:
{}

### Instruction:
{}

### Response:
{}
```

## Available sizes


| Branch | Bits | lm_head bits | VRAM (4k) | VRAM (8K) | VRAM (16k) | VRAM (32k) | Description |
| ----- | ---- | ------- | ------ | ------ | ------ | ------ | ------------ |
| [8_0](https://huggingface.co/bartowski/Replete-Coder-Llama3-8B-exl2/tree/8_0) | 8.0 | 8.0 | 10.1 GB | 10.5 GB | 11.5 GB | 13.6 GB | Maximum quality that ExLlamaV2 can produce, near unquantized performance. |
| [6_5](https://huggingface.co/bartowski/Replete-Coder-Llama3-8B-exl2/tree/6_5) | 6.5 | 8.0 | 8.9 GB | 9.3 GB | 10.3 GB | 12.4 GB | Very similar to 8.0, good tradeoff of size vs performance, **recommended**. |
| [5_0](https://huggingface.co/bartowski/Replete-Coder-Llama3-8B-exl2/tree/5_0) | 5.0 | 6.0 | 7.7 GB | 8.1 GB | 9.1 GB | 11.2 GB | Slightly lower quality vs 6.5, but usable on 8GB cards. |
| [4_25](https://huggingface.co/bartowski/Replete-Coder-Llama3-8B-exl2/tree/4_25) | 4.25 | 6.0 | 7.0 GB | 7.4 GB | 8.4 GB | 10.5 GB | GPTQ equivalent bits per weight, slightly higher quality. |
| [3_5](https://huggingface.co/bartowski/Replete-Coder-Llama3-8B-exl2/tree/3_5) | 3.5 | 6.0 | 6.4 GB | 6.8 GB | 7.8 GB | 9.9 GB | Lower quality, only use if you have to. |

## Download instructions

With git:

```shell
git clone --single-branch --branch 6_5 https://huggingface.co/bartowski/Replete-Coder-Llama3-8B-exl2 Replete-Coder-Llama3-8B-exl2-6_5
```

With huggingface hub (credit to TheBloke for instructions):

```shell
pip3 install huggingface-hub
```

To download a specific branch, use the `--revision` parameter. For example, to download the 6.5 bpw branch:

Linux:

```shell
huggingface-cli download bartowski/Replete-Coder-Llama3-8B-exl2 --revision 6_5 --local-dir Replete-Coder-Llama3-8B-exl2-6_5
```

Windows (which apparently doesn't like _ in folders sometimes?):

```shell
huggingface-cli download bartowski/Replete-Coder-Llama3-8B-exl2 --revision 6_5 --local-dir Replete-Coder-Llama3-8B-exl2-6.5
```

Want to support my work? Visit my ko-fi page here: https://ko-fi.com/bartowski