Instructions to use timm/samvit_large_patch16.sa1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/samvit_large_patch16.sa1b with timm:
import timm model = timm.create_model("hf_hub:timm/samvit_large_patch16.sa1b", pretrained=True) - Transformers
How to use timm/samvit_large_patch16.sa1b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="timm/samvit_large_patch16.sa1b")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/samvit_large_patch16.sa1b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d8383bf2c7fc1dfcb3ddc63097a388bb5791737a423ad151159dea5b6785ec00
- Size of remote file:
- 1.23 GB
- SHA256:
- c4d1022f3e4e026562f1535e65fe1861b4ada43d2cad0c5a8ad32571917d91f9
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