Instructions to use nmcco/16_gemma_flash with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nmcco/16_gemma_flash with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nmcco/16_gemma_flash", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4286a5495e73ee70aa2467b6daf00a6fd58cca5d8008c84ffe56cb2776ab2446
- Size of remote file:
- 34.4 MB
- SHA256:
- 8a78d92f7e020ab51b95ec99ec265945b280e46ab987cfbf7c777a7f929acece
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.