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Our model hasn't been fine-tuned through reinforcement learning from human feedback. The intention behind crafting this open-source model is to provide the research community with a non-restricted small model to explore vital safety challenges, such as reducing toxicity, understanding societal biases, enhancing controllability, and more.
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## Intended Uses
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Given the nature of the training data, the Phi-2 model is best suited for prompts using the QA format, the chat format, and the code format.
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Our model hasn't been fine-tuned through reinforcement learning from human feedback. The intention behind crafting this open-source model is to provide the research community with a non-restricted small model to explore vital safety challenges, such as reducing toxicity, understanding societal biases, enhancing controllability, and more.
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## How to Use
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Phi-2 has been integrated in the development version (4.37.0.dev) of `transformers`. Until the official version is released through `pip`, ensure that you are doing one of the following:
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* When loading the model, ensure that `trust_remote_code=True` is passed as an argument of the `from_pretrained()` function.
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* Update your local `transformers` to the development version: `pip uninstall -y transformers && pip install git+https://github.com/huggingface/transformers`. The previous command is an alternative to cloning and installing from the source.
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The current `transformers` version can be verified with: `pip list | grep transformers`.
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## Intended Uses
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Given the nature of the training data, the Phi-2 model is best suited for prompts using the QA format, the chat format, and the code format.
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