Instructions to use StemsOut/second_model_birds_notbirds_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StemsOut/second_model_birds_notbirds_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="StemsOut/second_model_birds_notbirds_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("StemsOut/second_model_birds_notbirds_model") model = AutoModelForImageClassification.from_pretrained("StemsOut/second_model_birds_notbirds_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from StemsOut/second_model_birds_notbirds_model: direct link, hf CLI and curl.
- Browser
- Download file 687 MB
-
https://huggingface.co/StemsOut/second_model_birds_notbirds_model/resolve/refs%2Fpr%2F1/optimizer.pt
- Command line
-
hf download hf://StemsOut/second_model_birds_notbirds_model@refs/pr/1/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/StemsOut/second_model_birds_notbirds_model/resolve/refs%2Fpr%2F1/optimizer.pt
687 MB
- Xet hash:
- 457aff79bb3b3f41b8cf99f601881ba04265e22e872a519ac37e5c0ac0b3d8ca
- Size of remote file:
- 687 MB
- SHA256:
- e8eef3c366fab6bd6125478eaefaf432fd77e32c7d36d0fcc7896ff86d550e09
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