Instructions to use kartmannXu/SmolVLM-500M-Instruct-bl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kartmannXu/SmolVLM-500M-Instruct-bl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="kartmannXu/SmolVLM-500M-Instruct-bl", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForVision2Seq model = AutoModelForVision2Seq.from_pretrained("kartmannXu/SmolVLM-500M-Instruct-bl", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from kartmannXu/SmolVLM-500M-Instruct-bl: direct link, hf CLI and curl.
- Browser
- Download file 486 Bytes
-
https://huggingface.co/kartmannXu/SmolVLM-500M-Instruct-bl/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://kartmannXu/SmolVLM-500M-Instruct-bl/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/kartmannXu/SmolVLM-500M-Instruct-bl/resolve/main/preprocessor_config.json
486 Bytes
| { | |
| "do_convert_rgb": true, | |
| "do_image_splitting": true, | |
| "do_normalize": true, | |
| "do_pad": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_processor_type": "Idefics3ImageProcessor", | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "max_image_size": { | |
| "longest_edge": 512 | |
| }, | |
| "processor_class": "Idefics3Processor", | |
| "resample": 1, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "longest_edge": 2048 | |
| } | |
| } | |