Instructions to use hilmansw/emotion_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hilmansw/emotion_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hilmansw/emotion_classification") 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("hilmansw/emotion_classification") model = AutoModelForImageClassification.from_pretrained("hilmansw/emotion_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hilmansw/emotion_classification: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/hilmansw/emotion_classification/resolve/main/training_args.bin
- Command line
-
hf download hf://hilmansw/emotion_classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hilmansw/emotion_classification/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- 3627545f9c80ba31d20096601acd9fda6563bdd1b84a80a7f4ce92c7a22bab15
- Size of remote file:
- 4.09 kB
- SHA256:
- 3ea00e88b072555ff83cb372e124a91b0952eb66792f963fc2480108e6ad13d6
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