Instructions to use timm/xcit_medium_24_p8_224.fb_dist_in1k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/xcit_medium_24_p8_224.fb_dist_in1k with timm:
import timm model = timm.create_model("hf-hub:timm/xcit_medium_24_p8_224.fb_dist_in1k", pretrained=True) - Transformers
How to use timm/xcit_medium_24_p8_224.fb_dist_in1k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="timm/xcit_medium_24_p8_224.fb_dist_in1k") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("timm/xcit_medium_24_p8_224.fb_dist_in1k") model = AutoModelForImageClassification.from_pretrained("timm/xcit_medium_24_p8_224.fb_dist_in1k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from timm/xcit_medium_24_p8_224.fb_dist_in1k: direct link, hf CLI and curl.
- Browser
- Download file 338 MB
-
https://huggingface.co/timm/xcit_medium_24_p8_224.fb_dist_in1k/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://timm/xcit_medium_24_p8_224.fb_dist_in1k/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/timm/xcit_medium_24_p8_224.fb_dist_in1k/resolve/main/pytorch_model.bin
338 MB
- Xet hash:
- f52291d007a1a339f9329c6ddc49a8bc90e95f94592eb3e8aa1f86debeac685d
- Size of remote file:
- 338 MB
- SHA256:
- b95f0e0eec8ad152dd7c74f2a16f978da903a0ac595b89c990494e243493c6ff
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