--- library_name: transformers datasets: - HuggingFaceH4/ultrachat_200k base_model: google/gemma-2b license: other license_name: gemma-terms-of-use license_link: https://ai.google.dev/gemma/terms --- [

](https://wandb.ai/llm_surgery/gemma-zephyr) # Gemma 2B Zephyr SFT The [Zephyr](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta) SFT recipe applied on top of Gemma 2B ## Model description - **Model type:** A 8.5B parameter GPT-like model fine-tuned on a mix of publicly available, synthetic datasets. - **Language(s) (NLP):** Primarily English - **Finetuned from model:** [google/gemma-7b](https://huggingface.co/google/gemma-2b) ## Recipe We trained using the [alignment handbook recipe](https://github.com/huggingface/alignment-handbook/blob/main/scripts/run_sft.py) and logging to W&B Visit the [W&B workspace here](https://wandb.ai/llm_surgery/gemma-zephyr?nw=nwusercapecape) ## License This model has the same license as the [original Gemma model collection](https://ai.google.dev/gemma/terms) ## Compute provided by Lambda Labs - 8xA100 80GB node - Around 2 hours to train