Instructions to use larity/pacman with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use larity/pacman with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="larity/pacman") 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("larity/pacman") model = AutoModelForImageClassification.from_pretrained("larity/pacman", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from larity/pacman: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/larity/pacman/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://larity/pacman/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/larity/pacman/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- fb874d9bf499af84bc7a024fb857a1a52ae8fa43282fdc8b64cd1a395ed814d4
- Size of remote file:
- 343 MB
- SHA256:
- f21b06a07dde3600468a3395e5d3479457787b180e9ab99163c097bdb92c25d9
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