Instructions to use facebook/regnet-x-006 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/regnet-x-006 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/regnet-x-006") 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-006") model = AutoModelForImageClassification.from_pretrained("facebook/regnet-x-006", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 10b57b9ec81505011e996302507af0b5ccb42872b217880a8c9c62a038d9305d
- Size of remote file:
- 25.2 MB
- SHA256:
- a23824ca7334c442f5f12be24ead78d2ff57a08ca609b06f4ea33c7c1e95a11c
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