---
library_name: peft
datasets:
- Squish42/bluemoon-fandom-1-1-rp-cleaned
- OpenLeecher/Teatime
- PygmalionAI/PIPPA
tags:
- not-for-all-audiences
- nsfw
---
## What is PetrolLoRA?
PetrolLoRA is the LoRA equivalent of [PetrolLM](https://huggingface.co/Norquinal/PetrolLM), without any of the instruction-tuning of the prior.

The dataset consists of 2800 samples, with the composition as follows:
* AICG Logs (~34%)
* PygmalionAI/PIPPA (~33%)
* Squish42/bluemoon-fandom-1-1-rp-cleaned (~29%)
* OpenLeecher/Teatime (~4%)

These samples were then back-filled using gpt-4/gpt-3.5-turbo-16k or otherwise converted to fit the prompt format.

## Prompt Format
The LoRA was finetuned with a prompt format similar to the original SuperHOT prototype:
```
---
style: roleplay
characters:
  [char]: [description]
summary: [scenario]
---
<chat_history>
Format:
[char]: [message]
Human: [message]
```

## Training procedure


The following `bitsandbytes` quantization config was used during training:
- quant_method: bitsandbytes
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float16

The following `bitsandbytes` quantization config was used during training:
- quant_method: bitsandbytes
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float16
### Framework versions

- PEFT 0.4.0

- PEFT 0.4.0