README.md

metadata

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
task_categories:
  - conversational
base_model: shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat
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.

Training Procedure

Training Procedure Raw Files

ALL the procedure are training on: Vast.ai

Hardware: 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 Environment

  {
  "DATA_DIRECTORY": "/workspace/",
  "JUPYTER_DIR": "/"
  }

ipynb file

Training Data

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

Dataset

• Minami-su/toxic-sft-zh
• llm-wizard/alpaca-gpt4-data-zh
• stephenlzc/stf-alpaca