Instructions to use Pranjal12345/Classification_Transformers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Pranjal12345/Classification_Transformers with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Pranjal12345/Classification_Transformers") 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("Pranjal12345/Classification_Transformers") model = AutoModelForImageClassification.from_pretrained("Pranjal12345/Classification_Transformers", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Browse files- config.json +1 -1
config.json
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"4": "engaged",
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"model_type": "
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"4": "engaged",
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"5": "frustated"
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"model_type": "vit_b_16"
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