Image Classification
Transformers
PyTorch
Safetensors
vit
vision
Generated from Trainer
Eval Results (legacy)
Instructions to use bortle/moon-detector-v5.a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bortle/moon-detector-v5.a with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="bortle/moon-detector-v5.a") 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("bortle/moon-detector-v5.a") model = AutoModelForImageClassification.from_pretrained("bortle/moon-detector-v5.a", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
Verified signature- Adding `safetensors` variant of this model (730976126206cec4f8e3f1b77faa362dc4a6e4b8) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>63a90cc
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update model card README.md
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End of training
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update model card README.md
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Training in progress, epoch 5
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Training in progress, epoch 4
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Training in progress, epoch 2
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Training in progress, epoch 1
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initial commit
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