Instructions to use agentmish/dog-emotion-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use agentmish/dog-emotion-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="agentmish/dog-emotion-classifier") 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("agentmish/dog-emotion-classifier") model = AutoModelForImageClassification.from_pretrained("agentmish/dog-emotion-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from agentmish/dog-emotion-classifier: direct link, hf CLI and curl.
- Browser
- Download file 5.84 kB
-
https://huggingface.co/agentmish/dog-emotion-classifier/resolve/main/training_args.bin
- Command line
-
hf download hf://agentmish/dog-emotion-classifier/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/agentmish/dog-emotion-classifier/resolve/main/training_args.bin
5.84 kB
- Xet hash:
- cb5bf9a4a8e585ca6bca6e098481d7aea7800bde796b85ecafa15f89884ac24b
- Size of remote file:
- 5.84 kB
- SHA256:
- 6f8889669508c7bf79d299227a2fe67f151553580eb34b3f18bb3aa746db7c50
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