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 pytorch_model.bin from leolin/my_bottle_model: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/leolin/my_bottle_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://leolin/my_bottle_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/leolin/my_bottle_model/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- ef317bffbcf8d400742459a15436c19f5353a5b244c8685ea44f2156d3aa71a6
- Size of remote file:
- 343 MB
- SHA256:
- 513f9c76c57b02d6763dd6031566827ad351a2826220146c8673fe2e51c6995d
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