Instructions to use qubvel-hf/debug_no_pad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use qubvel-hf/debug_no_pad with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="qubvel-hf/debug_no_pad")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("qubvel-hf/debug_no_pad") model = AutoModelForObjectDetection.from_pretrained("qubvel-hf/debug_no_pad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from qubvel-hf/debug_no_pad: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/qubvel-hf/debug_no_pad/resolve/main/training_args.bin
- Command line
-
hf download hf://qubvel-hf/debug_no_pad/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/qubvel-hf/debug_no_pad/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- ed8c4b935a7ad311678de7844a0e6ee1c1201bd29e79939786df9d294487a27d
- Size of remote file:
- 5.11 kB
- SHA256:
- d415ca6d7250ef6ffcfe0059c6288b51fc97a1b2db8b847c1d308c998be97ea9
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