Instructions to use ducnapa/apes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ducnapa/apes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ducnapa/apes") 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("ducnapa/apes") model = AutoModelForImageClassification.from_pretrained("ducnapa/apes", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ducnapa/apes: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/ducnapa/apes/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ducnapa/apes/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ducnapa/apes/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- 3994a13552b226732152d222c2ed31e1d1f6d4594c806bbdf5ff10e778a387c9
- Size of remote file:
- 343 MB
- SHA256:
- d59d2eb8e4e34c892ecb02ba79e15ac42b0e1b05076de929089cc12f0987abde
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