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This adapter was created by using the [PEFT](https://github.com/huggingface/peft) library and allowed the base model **BigScience/BLOOM 7B1** to be fine-tuned on the **Stanford's Alpaca Dataset** by using the method **LoRA**.
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## Model Description
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## Training data
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Alpaca is a dataset of 52,000 instructions and demonstrations generated by OpenAI's `text-davinci-003` engine. This instruction data can be used to conduct instruction-tuning for language models and make the language model follow instruction better.
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The authors built on the data generation pipeline from [Self-Instruct framework](https://github.com/yizhongw/self-instruct) and made the following modifications:
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### Supported Tasks and Leaderboards
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The Alpaca dataset designed for instruction training
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### Training procedure
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This adapter was created by using the [PEFT](https://github.com/huggingface/peft) library and allowed the base model **BigScience/BLOOM 7B1** to be fine-tuned on the **Stanford's Alpaca Dataset** by using the method **LoRA**.
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## Model Description
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BigScience Large Open-science Open-access Multilingual Language Model
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[BLOOM 7B1](https://huggingface.co/bigscience/bloom-7b1)
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## Training data
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Alpaca is a dataset of **52,000** instructions and demonstrations generated by OpenAI's `text-davinci-003` engine. This instruction data can be used to conduct instruction-tuning for language models and make the language model follow instruction better.
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The authors built on the data generation pipeline from [Self-Instruct framework](https://github.com/yizhongw/self-instruct) and made the following modifications:
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### Supported Tasks and Leaderboards
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The Alpaca dataset is designed for instruction training pre-trained language models.
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### Training procedure
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