Instructions to use nmcco/15_flashattn_gemma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nmcco/15_flashattn_gemma with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nmcco/15_flashattn_gemma", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from nmcco/15_flashattn_gemma: direct link, hf CLI and curl.
- Browser
- Download file 34.4 MB
-
https://huggingface.co/nmcco/15_flashattn_gemma/resolve/70ee89e1df295598fd8a47e963d7beffd400aaf7/tokenizer.json
- Command line
-
hf download hf://nmcco/15_flashattn_gemma@70ee89e1df295598fd8a47e963d7beffd400aaf7/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/nmcco/15_flashattn_gemma/resolve/70ee89e1df295598fd8a47e963d7beffd400aaf7/tokenizer.json
34.4 MB
- Xet hash:
- 4286a5495e73ee70aa2467b6daf00a6fd58cca5d8008c84ffe56cb2776ab2446
- Size of remote file:
- 34.4 MB
- SHA256:
- 8a78d92f7e020ab51b95ec99ec265945b280e46ab987cfbf7c777a7f929acece
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