Instructions to use fidhaph/finetuned-table with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fidhaph/finetuned-table with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="fidhaph/finetuned-table")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("fidhaph/finetuned-table") model = AutoModelForObjectDetection.from_pretrained("fidhaph/finetuned-table", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from fidhaph/finetuned-table: direct link, hf CLI and curl.
- Browser
- Download file 115 MB
-
https://huggingface.co/fidhaph/finetuned-table/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://fidhaph/finetuned-table/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/fidhaph/finetuned-table/resolve/main/pytorch_model.bin
115 MB
- Xet hash:
- 19ffcf7ea04d9fec68797d943d014c956abb8d4286a72d56f814b6cb6278ad39
- Size of remote file:
- 115 MB
- SHA256:
- d659e51023c2f1d949d794ddaac1acb92be6a6024a79ee17fc0685ec0b0ed363
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