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  ## ***See [our collection](https://huggingface.co/collections/unsloth/phi-4-all-versions-677eecf93784e61afe762afa) for versions of Phi-4 including GGUF, 4-bit & more formats.***
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  # Finetune Phi-4, Llama 3.3 2-5x faster with 70% less memory via Unsloth!
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- We have a free Google Colab Tesla T4 notebook for Phi-4 here: https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.1_(8B)-Alpaca.ipynb
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  [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/Discord%20button.png" width="200"/>](https://discord.gg/unsloth)
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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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- # unsloth/Phi-4
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- We have converted Phi-4 to Llama's architecture for improved ease of use, better fine-tuning, and greater accuracy. Also contains our bugfixes.
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  ## ✨ Finetune for Free
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  All notebooks are **beginner friendly**! Add your dataset, click "Run All", and you'll get a 2x faster finetuned model.
 
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  ## ***See [our collection](https://huggingface.co/collections/unsloth/phi-4-all-versions-677eecf93784e61afe762afa) for versions of Phi-4 including GGUF, 4-bit & more formats.***
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+ # unsloth/Phi-4
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+ We have converted Phi-4 to Llama's architecture for improved ease of use, better fine-tuning, and greater accuracy. Also contains [Unsloth's Phi-4 bugfixes](https://unsloth.ai/blog/phi4)
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  # Finetune Phi-4, Llama 3.3 2-5x faster with 70% less memory via Unsloth!
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+ We have a free Google Colab Tesla T4 notebook for Phi-4 here: https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Phi_4-Conversational.ipynb
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  [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/Discord%20button.png" width="200"/>](https://discord.gg/unsloth)
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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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  ## ✨ Finetune for Free
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  All notebooks are **beginner friendly**! Add your dataset, click "Run All", and you'll get a 2x faster finetuned model.