Instructions to use thelabel/image-labeling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thelabel/image-labeling with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="thelabel/image-labeling") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("thelabel/image-labeling") model = AutoModelForZeroShotImageClassification.from_pretrained("thelabel/image-labeling", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from thelabel/image-labeling: direct link, hf CLI and curl.
- Browser
- Download file 87 Bytes
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https://huggingface.co/thelabel/image-labeling/resolve/main/README.md
- Command line
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hf download hf://thelabel/image-labeling/README.md
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curl -L -o README.md https://huggingface.co/thelabel/image-labeling/resolve/main/README.md
87 Bytes
metadata
datasets:
- thelabel/image-labelling-dataset
pipeline_tag: image-classification