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--- |
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base_model: shenzhi-wang/Gemma-2-9B-Chinese-Chat |
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datasets: |
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- V3N0M/Jenna-50K-Alpaca-Uncensored |
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language: |
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- zh |
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- en |
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license: mit |
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pipeline_tag: text-generation |
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tags: |
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- text-generation-inference |
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- code |
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- unsloth |
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- uncensored |
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- finetune |
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task_categories: |
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- conversational |
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widget: |
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- text: 'Is this review positive or negative? Review: Best cast iron skillet you will |
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ever buy.' |
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example_title: Sentiment analysis |
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- text: Barack Obama nominated Hilary Clinton as his secretary of state on Monday. |
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He chose her because she had ... |
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example_title: Coreference resolution |
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- text: 'On a shelf, there are five books: a gray book, a red book, a purple book, |
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a blue book, and a black book ...' |
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example_title: Logic puzzles |
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- text: The two men running to become New York City's next mayor will face off in |
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their first debate Wednesday night ... |
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example_title: Reading comprehension |
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--- |
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## Model Details |
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### Model Description |
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- Using **shenzhi-wang/Gemma-2-9B-Chinese-Chat** as base model, and finetune the dataset as mentioned via **[unsloth](https://github.com/unslothai/unsloth)**. Makes the model uncensored. |
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- [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth) |
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### Training Code and Log |
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- [ipynb file](https://colab.research.google.com/assets/colab-badge.svg) |
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### Training Procedure Raw Files |
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- ALL the procedure are training on **[Runpod.io](https://www.runpod.io/)** |
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- **Hardware in Vast.ai**: |
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- **GPU**: 1 x A100 SXM 80G |
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- **CPU**: 16vCPU |
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- **RAM**: 251 GB |
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- **Disk Space To Allocate**：>150GB |
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- **Docker Image**: runpod/pytorch:2.2.0-py3.10-cuda12.1.1-devel-ubuntu22.04 |
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### Training Data |
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- **Base Model** |
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- [shenzhi-wang/Gemma-2-9B-Chinese-Chat](https://huggingface.co./shenzhi-wang/Gemma-2-9B-Chinese-Chat) |
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- **Dataset** |
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- [V3N0M/Jenna-50K-Alpaca-Uncensored](https://huggingface.co./datasets/V3N0M/Jenna-50K-Alpaca-Uncensored) |
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### Usage |
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```python |
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from transformers import pipeline |
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qa_model = pipeline("question-answering", model='stephenlzc/Gemma-2-9B-Chinese-Chat-Uncensored') |
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question = "How to make girlfreind laugh? please answer in Chinese." |
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qa_model(question = question) |
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``` |
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### |
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[<img src="https://img.buymeacoffee.com/button-api/?text=Buy me a coffee&emoji=&slug=chicongliau&button_colour=40DCA5&font_colour=ffffff&font_family=Poppins&outline_colour=000000&coffee_colour=FFDD00" width="200"/>](https://www.buymeacoffee.com/chicongliau) |
