Instructions to use facebook/regnet-y-320-seer-in1k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/regnet-y-320-seer-in1k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/regnet-y-320-seer-in1k") 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("facebook/regnet-y-320-seer-in1k") model = AutoModelForImageClassification.from_pretrained("facebook/regnet-y-320-seer-in1k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add feature extractor
Browse files- preprocessor_config.json +1 -1
preprocessor_config.json
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"resample": 3,
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"size":
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"resample": 3,
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