

NyakuraV2 - A Multi-Turn / Instruct Mix Fine-tuned Model.

Compute is thanks to my wallet, and runpod community pod 8x a40s for roughly 2 hours? Yeah that's it. 

Trained in ShareGPT dataset format due to multi-turn capabilities. 

use Vicuna 1.1 prompt format. Alpaca may work fine too, that format is like universal, may give sub-par results though..

I had much better results with the fp16 instead of GGUF, GGUF quants seem fucked? I don't know. May be on my side. Had so much nonsense input, had to wrangle settings until I had it coherent, it was working ***Really*** good. Fuck Yi models are a pain to work with.

You need better care with samplers when handling Yi Models. I have tested that Nyakura works well from 0 to 8k+ context, so I know it is not the model's fault.

Meow.

```
(Optional) System: <Prompt>

User: <Input>

Assistant:
```

*Example Prompt:*

```
User: Are you stand proud you're strong because you're nah I'd win, or are you nah I'd win because you're stand proud you're strong?

Assistant: You really should go to the doctor, I think you need help.
```

![Proud](https://i.gyazo.com/f8f3804ca59f74372c03c8ffe3ad6f43.png)
{"language": ["en"], "license": "cc-by-nc-4.0"}
transformers pytorch llama text-generation en license:cc-by-nc-4.0 autotrain_compatible endpoints_compatible text-generation-inference region:us