Finetune Mistral, Gemma, Llama 2 5x faster with 70% less memory via Unsloth! Directly quantized 4bit model with bitsandbytes . We have a Google Colab Tesla T4 notebook for TinyLlama with 4096 max sequence length RoPE Scaling here: https://colab.research.google.com/drive/1AZghoNBQaMDgWJpi4RbffGM1h6raLUj9?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 Gemma 7b ▶️ Start on Colab 2.4x faster 58% less Mistral 7b ▶️ Start on Colab 2.2x faster 62% less Llama 2 7b ▶️ Start on Colab 2.2x faster 43% 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 1.9x 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.
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