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 processor_config.json from kartmannXu/SmolVLM-500M-Instruct-bl: direct link, hf CLI and curl.
- Browser
- Download file 68 Bytes
-
https://huggingface.co/kartmannXu/SmolVLM-500M-Instruct-bl/resolve/main/processor_config.json
- Command line
-
hf download hf://kartmannXu/SmolVLM-500M-Instruct-bl/processor_config.json
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curl -L -o processor_config.json https://huggingface.co/kartmannXu/SmolVLM-500M-Instruct-bl/resolve/main/processor_config.json
68 Bytes
| { | |
| "image_seq_len": 64, | |
| "processor_class": "Idefics3Processor" | |
| } | |