Instructions to use Christian710/table_detection_detr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Christian710/table_detection_detr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="Christian710/table_detection_detr")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("Christian710/table_detection_detr") model = AutoModelForObjectDetection.from_pretrained("Christian710/table_detection_detr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model
This is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.a644f37
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Upload processor (#4)
- Upload processor (d06f3b29032e0324f2003cb5c42ec84e3f8e0746)cae3278 -
Upload processor (#6)
- Upload processor (fd12c0fdc216c8ba410d5df378b2a0d22679ad89)e594562 -
Upload TableTransformerForObjectDetection (#5)
- Upload TableTransformerForObjectDetection (829694ede96d13e42d79559327412b56ed31798d)9e129d2 -
initial commit
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