Reminder to use the dev version Transformers: pip install git+https://github.com/huggingface/transformers.git Finetune Gemma 2, Llama 3.1, Mistral 2 5x faster with 70% less memory via Unsloth! Directly quantized 4bit model with bitsandbytes . We have a Google Colab Tesla T4 notebook for Gemma 2 (2B) here: https://colab.research.google.com/drive/1weTpKOjBZxZJ5PQ Ql8i6ptAY2x FWVA?usp=sharing We have a Google Colab Tesla T4 notebook for Gemma 2 (9B) here: https://colab.research.google.com/drive/1vIrqH5uYDQwsJ4 OO3DErvuv4pBgVwk4?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 (8B) ▶️ Start on Colab 2.4x faster 58% less Gemma 2 (9B) ▶️ Start on Colab 2x faster 63% less Mistral (9B) ▶️ Start on Colab 2.2x faster 62% less Phi 3 (mini) ▶️ Start on Colab 2x faster 63% less TinyLlama ▶️ Start on Colab 3.9x faster 74% less CodeLlama (34B) A100 ▶️ Start on Colab 1.9x faster 27% less Mistral (7B) 1xT4 ▶️ Start on Kaggle 5x faster\ 62% less DPO Zephyr ▶️ Start on Colab 1.…
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