metadata
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, 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]
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