Instructions to use Loc/lucky-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Loc/lucky-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Loc/lucky-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("Loc/lucky-model") model = AutoModelForImageClassification.from_pretrained("Loc/lucky-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Loc/lucky-model: direct link, hf CLI and curl.
- Browser
- Download file 346 MB
-
https://huggingface.co/Loc/lucky-model/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://Loc/lucky-model@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Loc/lucky-model/resolve/refs%2Fpr%2F1/pytorch_model.bin
346 MB
- Xet hash:
- 932cd91d828354c94b22739d6561175801a6f9cdc3fee5a94871f80452413705
- Size of remote file:
- 346 MB
- SHA256:
- 5f17067668129d23b52524f90a805e7d9914c276d90a59a13ebe81a09e40ceca
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