Instructions to use ikim-uk-essen/BiomedCLIP_ViT_patch16_224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ikim-uk-essen/BiomedCLIP_ViT_patch16_224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="ikim-uk-essen/BiomedCLIP_ViT_patch16_224")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("ikim-uk-essen/BiomedCLIP_ViT_patch16_224") model = AutoModel.from_pretrained("ikim-uk-essen/BiomedCLIP_ViT_patch16_224", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a9a094ee43b4d730b1a74c468e3122bba7967c3abffbbd3d92ce351149311a83
- Size of remote file:
- 343 MB
- SHA256:
- be121e6c8d90db28450ca111c4befc802c0cce9d8feb09cfaef4097e44627036
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