Instructions to use mohitsha/resnet-tiny-beans-quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mohitsha/resnet-tiny-beans-quantized with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="mohitsha/resnet-tiny-beans-quantized") 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("mohitsha/resnet-tiny-beans-quantized") model = AutoModelForImageClassification.from_pretrained("mohitsha/resnet-tiny-beans-quantized", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from mohitsha/resnet-tiny-beans-quantized: direct link, hf CLI and curl.
- Browser
- Download file 28 Bytes
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https://huggingface.co/mohitsha/resnet-tiny-beans-quantized/resolve/main/README.md
- Command line
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hf download hf://mohitsha/resnet-tiny-beans-quantized/README.md
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curl -L -o README.md https://huggingface.co/mohitsha/resnet-tiny-beans-quantized/resolve/main/README.md
28 Bytes
| license: apache-2.0 | |