[EXL2](https://github.com/turboderp/exllamav2/tree/master#exllamav2) Quantization of [Gryphe's MythoMax L2 13B](https://huggingface.co/Gryphe/MythoMax-L2-13b).

Other quantized models are available from TheBloke: [GGML](https://huggingface.co/TheBloke/MythoMax-L2-13B-GGML) - [GPTQ](https://huggingface.co/TheBloke/MythoMax-L2-13B-GPTQ) - [GGUF](https://huggingface.co/TheBloke/MythoMax-L2-13B-GGUF) - [AWQ](https://huggingface.co/TheBloke/MythoMax-L2-13B-AWQ)





## Model details

| Branch                                                               | Bits | Perplexity | Desc                                                    |
|----------------------------------------------------------------------|------|------------|---------------------------------------------------------|
| [main](https://huggingface.co/R136a1/MythoMax-L2-13B-exl2/tree/main) | 5    | 6.1018     | Up to 6144 context size on T4 GPU                       |
| [6bit](https://huggingface.co/R136a1/MythoMax-L2-13B-exl2/tree/6bit) | 6    | 6.1182     | 4096 context size (tokens) on T4 GPU                    |
| [3bit](https://huggingface.co/R136a1/MythoMax-L2-13B-exl2/tree/3bit) | 3    | 6.3666     | Low bits quant while still good                         |
| [4bit](https://huggingface.co/R136a1/MythoMax-L2-13B-exl2/tree/4bit) | 4    | 6.1601     | Slightly better than 4bit GPTQ, ez 8K context on T4 GPU |
| -                                                                    | 7    | 6.1056     | 2048 max context size for T4 GPU                        |
| -                                                                    | 8    | 6.1027     | Just, why?                                              |

I'll upload the 7 and 8 bits quant if someone request it. (Idk y the 5 bits quant preplexity is lower than higher bits quant, I think I did something wrong?)

## Prompt Format

Alpaca format:
```
### Instruction:





### Response:
```