---
license: apache-2.0
datasets:
- totally-not-an-llm/everything-sharegptformat-morecleaned
language:
- en
pipeline_tag: text-generation
---
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:
```
GGML quants available [here](https://huggingface.co/TheBloke/Marx-3b-GGML).
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. | 36.5 |
| 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 |
| DROP (3-shot) | 5.22 |