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README.md
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---
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license: llama2
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datasets:
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- umd-zhou-lab/claude2_alpaca
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language:
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- en
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---
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# Model Card for umd-zhou-lab/recycled-alpaca-7b-v1.0
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<!-- Provide a quick summary of what the model is/does. -->
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This model is trained by fine-tuning llama-2 with claude2 alpaca data.
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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- **Developed by:** UMD Tianyi Zhou Lab
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- **Model type:** An auto-regressive language model based on the transformer architecture
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- **License:** Llama 2 Community License Agreement
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- **Finetuned from model:** [meta-llama/Llama-2-7b](https://huggingface.co/meta-llama/Llama-2-7b)
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### Model Sources
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<!-- Provide the basic links for the model. -->
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- **GitHub:** [Claude2-Alpaca](https://github.com/Lichang-Chen/claude2-alpaca)
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- **Data:** [claude2_alpaca](https://huggingface.co/datasets/umd-zhou-lab/claude2_alpaca)
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## Uses
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The primary use of this model is research on large language models and chatbots.
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The primary intended users of the model are researchers and hobbyists in natural language processing, machine learning, and artificial intelligence.
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## Training
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We use the prompt from [Stanford Alpaca](https://github.com/tatsu-lab/stanford_alpaca)
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| Hyperparameter | Global Batch Size | Learning rate | Epochs | Max length | Weight decay |
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| --- | ---: | ---: | ---: | ---: | ---: |
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| Model (7B) | 128 | 2e-5 | 3 | 4096 | 0 |
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## Citation
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Please consider citing our paper if you think our codes, data, or models are useful. Thank you!
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```
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@misc{claude2-alpaca,
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author = {Lichang Chen and Khalid Saifullah and Ming Li and Tianyi Zhou and Heng Huang},
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title = {Claude2-Alpaca: Instruction tuning datasets distilled from claude},
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year = {2023},
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publisher = {GitHub},
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journal = {GitHub repository},
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howpublished = {\url{https://github.com/Lichang-Chen/claude2-alpaca}},
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}
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```
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