README.md · stephenlzc/Mistral-7B-v0.3-Chinese-Chat-uncensored at 7738e38e522301a0061617ea10664b87e02cb494

metadata

base_model: shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat
datasets:
  - Minami-su/toxic-sft-zh
  - llm-wizard/alpaca-gpt4-data-zh
  - stephenlzc/stf-alpaca
language:
  - zh
license: mit
pipeline_tag: text-generation
tags:
  - text-generation-inference
  - code
  - unsloth
  - uncensored
  - finetune
task_categories:
  - conversational
widget:
  - text: >-
      Is this review positive or negative? Review: Best cast iron skillet you
      will ever buy.
    example_title: Sentiment analysis
  - text: >-
      Barack Obama nominated Hilary Clinton as his secretary of state on Monday.
      He chose her because she had ...
    example_title: Coreference resolution
  - text: >-
      On a shelf, there are five books: a gray book, a red book, a purple book,
      a blue book, and a black book ...
    example_title: Logic puzzles
  - text: >-
      The two men running to become New York City's next mayor will face off in
      their first debate Wednesday night ...
    example_title: Reading comprehension

Model Details

Model Description

Using shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat as base model, and finetune the dataset as mentioned via unsloth. Makes the model uncensored.

Training Code

Training Procedure Raw Files

ALL the procedure are training on Vast.ai
Hardware in Vast.ai:
- GPU: 1x A100 SXM4 80GB
- CPU: AMD EPYC 7513 32-Core Processor
- RAM: 129 GB
- Docker Image: pytorch/pytorch:2.2.0-cuda12.1-cudnn8-devel
- Download the ipynb file.

Training Data

Base Model
- shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat
Dataset