Instructions to use oscarmak/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oscarmak/output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="oscarmak/output")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("oscarmak/output") model = AutoModelForObjectDetection.from_pretrained("oscarmak/output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from oscarmak/output: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/oscarmak/output/resolve/main/training_args.bin
- Command line
-
hf download hf://oscarmak/output/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/oscarmak/output/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- 2fa792f1ef8a2372e9666e1f26e5f0d85c3d51ffc083974c09104c35aa9ec630
- Size of remote file:
- 4.54 kB
- SHA256:
- 468672d0632a7403380ccb8fac71544426263879bc02cbd790983e6709a8868e
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