Instructions to use leolin/my_bottle_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leolin/my_bottle_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="leolin/my_bottle_model") 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("leolin/my_bottle_model") model = AutoModelForImageClassification.from_pretrained("leolin/my_bottle_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from leolin/my_bottle_model: direct link, hf CLI and curl.
- Browser
- Download file 3.45 kB
-
https://huggingface.co/leolin/my_bottle_model/resolve/main/training_args.bin
- Command line
-
hf download hf://leolin/my_bottle_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/leolin/my_bottle_model/resolve/main/training_args.bin
3.45 kB
- Xet hash:
- 67d72dcec359810511304c1375e864c6896ee7e966f093ab59e943ca46d3edd5
- Size of remote file:
- 3.45 kB
- SHA256:
- 016a79456d72029d7fda68e0bf6f4b4a47733af017fe40de9bfc00724f7ad5f1
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