Instructions to use merve/rfdetr-docvqa-media3-trainval-agree1-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use merve/rfdetr-docvqa-media3-trainval-agree1-medium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="merve/rfdetr-docvqa-media3-trainval-agree1-medium")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("merve/rfdetr-docvqa-media3-trainval-agree1-medium") model = AutoModelForObjectDetection.from_pretrained("merve/rfdetr-docvqa-media3-trainval-agree1-medium") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b687028770a78f1328ec82fa16bf13ab57445ba5eabdd5f7512945e2f1601b71
- Size of remote file:
- 5.27 kB
- SHA256:
- a551107d4bc55035403f2cecfbad104ac820c85252dcb4983cc5e8c0e2eedb85
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