Instructions to use belfner/vit_large_patch16_lingbot.robbyant with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use belfner/vit_large_patch16_lingbot.robbyant with timm:
import timm model = timm.create_model("hf_hub:belfner/vit_large_patch16_lingbot.robbyant", pretrained=True) - Transformers
How to use belfner/vit_large_patch16_lingbot.robbyant with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="belfner/vit_large_patch16_lingbot.robbyant")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("belfner/vit_large_patch16_lingbot.robbyant", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 973cd1c4eba80977796e726a6c19d9e1875ab565f1efa9c28a040d991c24c865
- Size of remote file:
- 1.21 GB
- SHA256:
- b8a7ccc65491d472fdfc131ed1bf29316ca229920920821b8762525a9b885690
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