Instructions to use timm/vit_huge_patch14_clip_224.dfn5b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/vit_huge_patch14_clip_224.dfn5b with timm:
import timm model = timm.create_model("hf_hub:timm/vit_huge_patch14_clip_224.dfn5b", pretrained=True) - Transformers
How to use timm/vit_huge_patch14_clip_224.dfn5b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="timm/vit_huge_patch14_clip_224.dfn5b")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/vit_huge_patch14_clip_224.dfn5b", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eb2a698fcf5e89aad225adc3ee6717332361b3cbb533ebf44e912c1a93edbca7
- Size of remote file:
- 2.53 GB
- SHA256:
- 96812ed4919c501a820525888366ed5065fcb88468e0da7f5633ce095ccefd5d
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