Instructions to use howdyaendra/xblock-large-patch1-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use howdyaendra/xblock-large-patch1-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="howdyaendra/xblock-large-patch1-224") 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("howdyaendra/xblock-large-patch1-224") model = AutoModelForImageClassification.from_pretrained("howdyaendra/xblock-large-patch1-224", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from howdyaendra/xblock-large-patch1-224: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/howdyaendra/xblock-large-patch1-224/resolve/main/training_args.bin
- Command line
-
hf download hf://howdyaendra/xblock-large-patch1-224/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/howdyaendra/xblock-large-patch1-224/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- d167aa2990e630ee10816e8e7f9f36d9bc6bd7c5b74af74d4e8b4f99a993d85b
- Size of remote file:
- 4.92 kB
- SHA256:
- a36bcaf4b017105a6b5c611351b3463f4ec882dc8f5f08694d8c26469765c61d
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