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:
- f4ec14d24fd6f4ebdbc5f303ad50c9fa710fc6b43a052ece38b1e8e6dd4f69b6
- Size of remote file:
- 134 MB
- SHA256:
- 21db115ceefcd91e7e1400e0c59c81742e23c4440a8ef329ab1e0915e89bfcb2
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