README.md

---
license: apache-2.0
datasets:
- totally-not-an-llm/everything-sharegptformat-morecleaned
language:
- en
pipeline_tag: text-generation
---

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This is [OpenLLaMA 3B V2](https://huggingface.co/openlm-research/open_llama_3b_v2) finetuned on [EverythingLM Data(ShareGPT format more cleaned)](https://huggingface.co/datasets/totally-not-an-llm/everything-sharegptformat-morecleaned) for 1 epochs.

Prompt template:
```
### HUMAN:
{prompt}

### RESPONSE:
<leave a newline for the model to answer>
```
GGML quants available [here](https://huggingface.co/TheBloke/Marx-3b-GGML).</br>
GPTQ quants available [here](https://huggingface.co/TheBloke/Marx-3b-GPTQ).

Note: Don't expect this model to be good, I was just starting out to finetune. So don't roast me please!

# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_acrastt__Marx-3B)

| Metric                | Value                     |
|-----------------------|---------------------------|
| Avg.                  | 41.71   |
| ARC (25-shot)         | 43.17          |
| HellaSwag (10-shot)   | 72.68    |
| MMLU (5-shot)         | 28.46         |
| TruthfulQA (0-shot)   | 39.09   |
| Winogrande (5-shot)   | 65.59   |
| GSM8K (5-shot)        | 1.29        |