Instructions to use kmewhort/resnet34-sketch-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kmewhort/resnet34-sketch-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="kmewhort/resnet34-sketch-classifier") 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("kmewhort/resnet34-sketch-classifier") model = AutoModelForImageClassification.from_pretrained("kmewhort/resnet34-sketch-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download trainer_state.json from kmewhort/resnet34-sketch-classifier: direct link, hf CLI and curl.
- Browser
- Download file 2.17 MB
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https://huggingface.co/kmewhort/resnet34-sketch-classifier/resolve/main/trainer_state.json
- Command line
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hf download hf://kmewhort/resnet34-sketch-classifier/trainer_state.json
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curl -L -o trainer_state.json https://huggingface.co/kmewhort/resnet34-sketch-classifier/resolve/main/trainer_state.json
2.17 MB
File too large to display, you can check the raw version instead.