Instructions to use kl2420/detr_table with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kl2420/detr_table with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="kl2420/detr_table")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("kl2420/detr_table") model = AutoModelForObjectDetection.from_pretrained("kl2420/detr_table", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from kl2420/detr_table: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/kl2420/detr_table/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://kl2420/detr_table/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/kl2420/detr_table/resolve/main/pytorch_model.bin
167 MB
- Xet hash:
- bc9ea2476118c02fb31a05d303994d2f0f60cd3d2f39246ea7793e7da796530c
- Size of remote file:
- 167 MB
- SHA256:
- 162f6283eb1a7929df050276a01b6f09976a5ef86f3011ecab6abb3e7eab5805
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