Instructions to use Amogh06/DeTr-Table-Detection-Model-public2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Amogh06/DeTr-Table-Detection-Model-public2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="Amogh06/DeTr-Table-Detection-Model-public2")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("Amogh06/DeTr-Table-Detection-Model-public2") model = AutoModelForObjectDetection.from_pretrained("Amogh06/DeTr-Table-Detection-Model-public2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Amogh06/DeTr-Table-Detection-Model-public2: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/Amogh06/DeTr-Table-Detection-Model-public2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Amogh06/DeTr-Table-Detection-Model-public2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Amogh06/DeTr-Table-Detection-Model-public2/resolve/main/pytorch_model.bin
167 MB
- Xet hash:
- 713734a32c6b72fcb6d7166421077125a232a770b010e22cca4c987334d4d928
- Size of remote file:
- 167 MB
- SHA256:
- 38a650a93f97a6826e16b7ddbf82e757507561cde8a6c4d693545a2244e875ae
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