Instructions to use kaidhar/gemma-3-kd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kaidhar/gemma-3-kd with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("kaidhar/gemma-3-kd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download processor_config.json from kaidhar/gemma-3-kd: direct link, hf CLI and curl.
- Browser
- Download file 70 Bytes
-
https://huggingface.co/kaidhar/gemma-3-kd/resolve/main/processor_config.json
- Command line
-
hf download hf://kaidhar/gemma-3-kd/processor_config.json
-
curl -L -o processor_config.json https://huggingface.co/kaidhar/gemma-3-kd/resolve/main/processor_config.json
70 Bytes
| { | |
| "image_seq_length": 256, | |
| "processor_class": "Gemma3Processor" | |
| } | |