Instructions to use BF667/gemma-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BF667/gemma-3 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("BF667/gemma-3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download processor_config.json from BF667/gemma-3: direct link, hf CLI and curl.
- Browser
- Download file 98 Bytes
-
https://huggingface.co/BF667/gemma-3/resolve/main/processor_config.json
- Command line
-
hf download hf://BF667/gemma-3/processor_config.json
-
curl -L -o processor_config.json https://huggingface.co/BF667/gemma-3/resolve/main/processor_config.json
98 Bytes
| { | |
| "audio_seq_length": 188, | |
| "image_seq_length": 256, | |
| "processor_class": "Gemma3nProcessor" | |
| } | |