README.md

---
license: other
license_name: yi-license
license_link: LICENSE
---

## Model description

Yi-34B model fine-tuned on AEZAKMI v1 dataset that is derived from airoboros 2.2.1 and airoboros 2.2. Finetuned with axolotl, using qlora and nf4 double quant, 1 epoch, batch size 1, lr 0.00007, lr scheduler constant. Training took around 33 hours on single local RTX 3090 Ti.
I had power target set to 320W for the GPU, and while I didn't measure power at the wall, it was probably something around 500W. Given the average electricity price in my region, this training run cost me around $3. This was my first attempt at training Yi-34B with this dataset.
Main feature of this model is that it's output should be free of refusals and it feels somehow more natural than airoboros. Prompt format is standard chatml. Don't expect it to be good at math, riddles or be crazy smart. My end goal with AEZAKMI is to create a cozy free chatbot.

## Prompt Format

I recommend using ChatML format, as this was used during fine-tune
Here's a prompt format you should use, you can set a different system message, model seems to respect that fine, so it wasn't overfitted.

```
<|im_start|>system
A chat.<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
```

## Intended uses & limitations

Use is limited by Yi license

## Known Issues

I recommend to set repetition penalty to something around 1.05 to avoid repetition. So far I had good experience running this model with temperature 1.2.
Multi-turn conversations could be a bit better, if you ask it to re-write something with some fixes it will have a tendency to just repeat the previous response verbatim without any improvements - this is especially noticeable with repp 1.0
There is still some gptslop left - some responses will have last paragraph with text "Remember that bla bla bla", I will try to get rid of it in the next version of the dataset.
Stories have ChatGPT like paragraph spacing, I will try to introduce a bit more stories that have long paragraphs in the next dataset version.

## Upcoming

I will release adapter files and maybe exllama v2 quant shortly.