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---
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
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. Makes the model uncensored.
## Training Code
[](https://colab.research.google.com/drive/1K9stY8LMVcySG0jDMYZdWQCFPfoDFBL-?usp=sharing)
## Training Procedure Raw Files
ALL the procedure are training on **[Vast.ai](https://cloud.vast.ai/?ref_id=138637)**
**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
**[ipynb file](https://huggingface.co/stephenlzc/dolphin-llama3-zh-cn-uncensored/blob/main/config.json)**
### Training Data
**Base Model**
[shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat](https://huggingface.co/shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat)
**Dataset**
- [Minami-su/toxic-sft-zh](https://huggingface.co/datasets/Minami-su/toxic-sft-zh)
- [llm-wizard/alpaca-gpt4-data-zh](https://huggingface.co/datasets/llm-wizard/alpaca-gpt4-data-zh)
- [stephenlzc/stf-alpaca](https://huggingface.co/datasets/stephenlzc/stf-alpaca) |