Instructions to use timm/vit_base_patch32_clip_224.openai with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/vit_base_patch32_clip_224.openai with timm:
import timm model = timm.create_model("hf_hub:timm/vit_base_patch32_clip_224.openai", pretrained=True) - Transformers
How to use timm/vit_base_patch32_clip_224.openai with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/vit_base_patch32_clip_224.openai", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa814f2bdcc62faca970a60fb35a8cc84a8c09d4209c0e4ea4341148a4c823df
- Size of remote file:
- 605 MB
- SHA256:
- 9ecdaef325b20e7283dc6a32f92aa638d100899e4f084c2462d3832eeea0b26e
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