Instructions to use davabbb/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davabbb/output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="davabbb/output")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("davabbb/output") model = AutoModelForObjectDetection.from_pretrained("davabbb/output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from davabbb/output: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/davabbb/output/resolve/main/training_args.bin
- Command line
-
hf download hf://davabbb/output/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/davabbb/output/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- 21f6b688006c74cdb6adf701275fc8857134a8af0f5a4e027bd4bbf54472fa36
- Size of remote file:
- 5.11 kB
- SHA256:
- 8684b23e7d86a9013d348c1f88e0ea0a2865f3ace171dfe3f3ff4145b826b45a
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