Instructions to use facebook/regnet-x-160 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/regnet-x-160 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/regnet-x-160") 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("facebook/regnet-x-160") model = AutoModelForImageClassification.from_pretrained("facebook/regnet-x-160", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#2)
- Adding `safetensors` variant of this model (0c65e0fe3b67949639d6c11727704571c7f2307b) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>fe40b7d
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Add TF weights (#1)
joaogante- Add TF weights (f243d548ed5c89f2a23bccfc492a664bdec6ed83)30ed473
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Upload README.md
2e0d7c2
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Add feature extractor
f256c51 -
Add model
b7d603e -
initial commit
1e7038c