File size: 1,734 Bytes
fbbf242 52a973b 2050c35 52a973b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 |
---
base_model: migtissera/Tess-34B-v1.4
inference: false
license: other
license_name: yi-license
license_link: https://huggingface.co/01-ai/Yi-34B/blob/main/LICENSE
metrics:
- accuracy
---
[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
An instruct based fine tune of [migtissera/Tess-34B-v1.4](https://huggingface.co/migtissera/Tess-34B-v1.4).
It works well with long system prompts.
It isn't generic in a sense that it shouldn't be used for story telling, for example, but only for reasoning and text comprehension.
This model is trained on a private dataset. The high GSM8K score is **NOT** because of the MetaMath dataset.
# Prompt Format:
```
SYSTEM: <ANY SYSTEM CONTEXT>
USER:
ASSISTANT:
```
Quants:
[TheBloke/Pallas-0.5-GGUF](https://huggingface.co/TheBloke/Pallas-0.5-GGUF)
[TheBloke/Pallas-0.5-AWQ](https://huggingface.co/TheBloke/Pallas-0.5-AWQ)
[TheBloke/Pallas-0.5-GPTQ](https://huggingface.co/TheBloke/Pallas-0.5-GPTQ)
[LoneStriker/Pallas-0.5-3.0bpw-h6-exl2](https://huggingface.co/LoneStriker/Pallas-0.5-3.0bpw-h6-exl2)
[LoneStriker/Pallas-0.5-4.0bpw-h6-exl2](https://huggingface.co/LoneStriker/Pallas-0.5-4.0bpw-h6-exl2)
[LoneStriker/Pallas-0.5-4.65bpw-h6-exl2](https://huggingface.co/LoneStriker/Pallas-0.5-4.65bpw-h6-exl2)
[LoneStriker/Pallas-0.5-5.0bpw-h6-exl2](https://huggingface.co/LoneStriker/Pallas-0.5-5.0bpw-h6-exl2)
[LoneStriker/Pallas-0.5-6.0bpw-h6-exl2](https://huggingface.co/LoneStriker/Pallas-0.5-6.0bpw-h6-exl2)
[LoneStriker/Pallas-0.5-8.0bpw-h8-exl2](https://huggingface.co/LoneStriker/Pallas-0.5-8.0bpw-h8-exl2) |