Instructions to use raffaelsiregar/emotions-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use raffaelsiregar/emotions-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="raffaelsiregar/emotions-classification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("raffaelsiregar/emotions-classification") model = AutoModelForImageClassification.from_pretrained("raffaelsiregar/emotions-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 73a853e16ed144c21b66c3569ea90d5164f6cb821a475d43115f61a22215c456
- Size of remote file:
- 5.11 kB
- SHA256:
- bd73360147ebc99cf9b18797c73e3ca1b6a144dbe9fdefe8690a82c5b739003e
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