Instructions to use Nonem100/Test-Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nonem100/Test-Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Nonem100/Test-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("Nonem100/Test-Model") model = AutoModelForImageClassification.from_pretrained("Nonem100/Test-Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Nonem100/Test-Model: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/Nonem100/Test-Model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Nonem100/Test-Model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Nonem100/Test-Model/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- d4ae2c99a9e6f21f8779876dfa2f55391de0228d591bd7dbe58684a434ae70d7
- Size of remote file:
- 343 MB
- SHA256:
- 78886aaca2b30c2008b86af9866880c1cde3bac7ea583af304143ba58645bafb
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