unsloth/gemma-2-9b

Reminder to use the dev version Transformers:

pip install git+https://github.com/huggingface/transformers.git

Finetune Gemma, Llama 3, 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 (9B) here: https://colab.research.google.com/drive/1vIrqH5uYDQwsJ4-OO3DErvuv4pBgVwk4?usp=sharing

<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/Discord%20button.png" width="200"/> <img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/buy%20me%20a%20coffee%20button.png" width="200"/> <img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>

✨ 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.

• —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.