Instructions to use mjun0812/resnext101d_32x4d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use mjun0812/resnext101d_32x4d with timm:
import timm model = timm.create_model("hf-hub:mjun0812/resnext101d_32x4d", pretrained=True) - Transformers
How to use mjun0812/resnext101d_32x4d with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="mjun0812/resnext101d_32x4d") 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("mjun0812/resnext101d_32x4d") model = AutoModelForImageClassification.from_pretrained("mjun0812/resnext101d_32x4d", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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