Finetune Llama 3.1, Gemma 2, Mistral 2 5x faster with 70% less memory via Unsloth! We have a free Google Colab Tesla T4 notebook for Llama 3.1 (8B) here: https://colab.research.google.com/drive/1Ys44kVvmeZtnICzWz0xgpRnrIOjZAuxp?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 3.2 (3B) ▶️ Start on Colab 2.4x faster 58% less Llama 3.2 (11B vision) ▶️ Start on Colab 2x faster 60% less Llama 3.1 (8B) ▶️ Start on Colab 2.4x faster 58% less Qwen2 VL (7B) ▶️ Start on Colab 1.8x faster 60% less Qwen2.5 (7B) ▶️ Start on Colab 2x faster 60% 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 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…
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