Instructions to use AiHub4MSRH-Hash/hash-MedGemma-1.5-4B-8bit-multilingual-it-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AiHub4MSRH-Hash/hash-MedGemma-1.5-4B-8bit-multilingual-it-3 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AiHub4MSRH-Hash/hash-MedGemma-1.5-4B-8bit-multilingual-it-3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download processor_config.json from AiHub4MSRH-Hash/hash-MedGemma-1.5-4B-8bit-multilingual-it-3: direct link, hf CLI and curl.
- Browser
- Download file 519 Bytes
-
https://huggingface.co/AiHub4MSRH-Hash/hash-MedGemma-1.5-4B-8bit-multilingual-it-3/resolve/main/processor_config.json
- Command line
-
hf download hf://AiHub4MSRH-Hash/hash-MedGemma-1.5-4B-8bit-multilingual-it-3/processor_config.json
-
curl -L -o processor_config.json https://huggingface.co/AiHub4MSRH-Hash/hash-MedGemma-1.5-4B-8bit-multilingual-it-3/resolve/main/processor_config.json
519 Bytes
| { | |
| "image_processor": { | |
| "do_convert_rgb": true, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_processor_type": "Gemma3ImageProcessor", | |
| "image_seq_length": 256, | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "resample": 2, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "height": 896, | |
| "width": 896 | |
| } | |
| }, | |
| "image_seq_length": 256, | |
| "processor_class": "Gemma3Processor" | |
| } | |