Instructions to use timm/convnext_large.fb_in22k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/convnext_large.fb_in22k with timm:
import timm model = timm.create_model("hf_hub:timm/convnext_large.fb_in22k", pretrained=True) - Transformers
How to use timm/convnext_large.fb_in22k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="timm/convnext_large.fb_in22k") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/convnext_large.fb_in22k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d0fc2b609879c762409571d75f394f4ed458afa715327d7c6bbf57111dd13ba3
- Size of remote file:
- 919 MB
- SHA256:
- 5c09bf09db5f3c50767ca3f4e6db95fd45889fa8be6e4ec7d6f2dedf25cc8253
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