Instructions to use kittendev/visual_emotional_analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kittendev/visual_emotional_analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="kittendev/visual_emotional_analysis") 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("kittendev/visual_emotional_analysis") model = AutoModelForImageClassification.from_pretrained("kittendev/visual_emotional_analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files- pytorch_model.bin +2 -2
- training_args.bin +1 -1
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