Instructions to use BarelyFunctionalCode/Janus-Pro-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BarelyFunctionalCode/Janus-Pro-1B with Transformers:
# Load model directly from transformers import MultiModalityCausalLM model = MultiModalityCausalLM.from_pretrained("BarelyFunctionalCode/Janus-Pro-1B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from BarelyFunctionalCode/Janus-Pro-1B: direct link, hf CLI and curl.
- Browser
- Download file 346 Bytes
-
https://huggingface.co/BarelyFunctionalCode/Janus-Pro-1B/resolve/refs%2Fpr%2F1/preprocessor_config.json
- Command line
-
hf download hf://BarelyFunctionalCode/Janus-Pro-1B@refs/pr/1/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/BarelyFunctionalCode/Janus-Pro-1B/resolve/refs%2Fpr%2F1/preprocessor_config.json
346 Bytes
| { | |
| "background_color": [ | |
| 127, | |
| 127, | |
| 127 | |
| ], | |
| "do_normalize": true, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_processor_type": "VLMImageProcessor", | |
| "image_size": 384, | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "min_size": 14, | |
| "processor_class": "VLChatProcessor", | |
| "rescale_factor": 0.00392156862745098 | |
| } | |