Instructions to use tcvrishank/fun with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tcvrishank/fun with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="tcvrishank/fun") 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("tcvrishank/fun") model = AutoModelForImageClassification.from_pretrained("tcvrishank/fun", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9eb5692633ed4129ef6b7db3083f3eab9c43f986f2ddeef13904e250d72131f0
- Size of remote file:
- 343 MB
- SHA256:
- 422bdddc345483a9de06c3d843acf40c47a850f103e76aa7d58673f479dbd524
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