Instructions to use facebook/regnet-x-032 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/regnet-x-032 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/regnet-x-032") 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-x-032") model = AutoModelForImageClassification.from_pretrained("facebook/regnet-x-032") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 835a08aa77af34c769308a89aa147275afaf7cba4f05a6f2a9721df3cd62ebbc
- Size of remote file:
- 61.6 MB
- SHA256:
- 26b9068452a5345b43693db36411ed072378e97e42b1fcb802c494b2241da363
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