See our collection for all versions of Llama 3.2 including GGUF, 4 bit and original 16 bit formats. Unsloth's Dynamic 4 bit Quants selectively avoids quantizing certain parameters, greatly increase accuracy than standard 4 bit. See our full collection of Unsloth quants on Hugging Face here. Finetune Llama 3.2, Gemma 2, Mistral 2 5x faster with 70% less memory via Unsloth! We have a free Google Colab Tesla T4 notebook for Llama 3.2 (3B) here: https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.1 (8B) Alpaca.ipynb unsloth/Llama 3.2 3B unsloth bnb 4bit For more details on the model, please go to Meta's original model card ✨ 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 Conversational.ipynb) 2.4x faster 58% less Llama 3.2 (11B vision) ▶️ Start on Colab Vision.ipynb) 2x faster 60% less Qwen2 VL (7B) ▶️ Start on Colab Vision.ipynb) 1.8x faster 60% less Qwen2.5 (7B) ▶️ Start on Colab Alpaca.ipynb) 2x faster 60% less Llama 3…
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