Reminder to use the dev version Transformers:
pip install git+https://github.com/huggingface/transformers.git
Finetune Phi-3.5, Llama 3.1, Mistral 2-5x faster with 70% less memory via Unsloth!
We have a free Google Colab Tesla T4 notebook for Phi-3.5 (mini) here: https://colab.research.google.com/drive/1lN6hPQveB_mHSnTOYifygFcrO8C1bxq4?usp=sharing
✨ Finetune for Free
All notebooks are beginner friendly! Add your dataset, click "Run All", and you'll get a 2x faster finetuned model which can be exported to GGUF, vLLM or uploaded to Hugging Face.
Unsloth supports | Free Notebooks | Performance | Memory use |
---|---|---|---|
Llama-3.1 8b | ▶️ Start on Colab | 2.4x faster | 58% less |
Phi-3.5 (mini) | ▶️ Start on Colab | 2x faster | 50% less |
Gemma-2 9b | ▶️ Start on Colab | 2.4x faster | 58% less |
Mistral 7b | ▶️ Start on Colab | 2.2x faster | 62% less |
TinyLlama | ▶️ Start on Colab | 3.9x faster | 74% less |
DPO - Zephyr | ▶️ Start on Colab | 1.9x faster | 19% less |
- This conversational notebook is useful for ShareGPT ChatML / Vicuna templates.
- This text completion notebook is for raw text. This DPO notebook replicates Zephyr.
- * Kaggle has 2x T4s, but we use 1. Due to overhead, 1x T4 is 5x faster.
Special Thanks
A huge thank you to Microsoft AI and Phi team for creating and releasing these models.
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