Instructions to use mlciv/gemma-3-1b-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mlciv/gemma-3-1b-it with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mlciv/gemma-3-1b-it", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6dbda7ecac9605b9f8f8426ff4b166e16319a6cdc4f07584bd929cba77b56afb
- Size of remote file:
- 6.23 kB
- SHA256:
- 45cf04c6112f5cdb76ba64f450afb2008b2f79483956671701202dacbe185b42
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.