Object Detection
Transformers
Safetensors
detr
computer-vision
text-detection
historical-documents
Eval Results (legacy)
Instructions to use harness-race/opencode-r2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harness-race/opencode-r2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="harness-race/opencode-r2")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("harness-race/opencode-r2") model = AutoModelForObjectDetection.from_pretrained("harness-race/opencode-r2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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report validation results
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fine-tuned DETR on loc_beyond_words
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fix: move labels to device
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update train.py
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add training script
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add model card
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initial commit
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