Instructions to use jmgrodriguez/main_hf_cppe5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jmgrodriguez/main_hf_cppe5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="jmgrodriguez/main_hf_cppe5")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("jmgrodriguez/main_hf_cppe5") model = AutoModelForObjectDetection.from_pretrained("jmgrodriguez/main_hf_cppe5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jmgrodriguez/main_hf_cppe5: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/jmgrodriguez/main_hf_cppe5/resolve/main/training_args.bin
- Command line
-
hf download hf://jmgrodriguez/main_hf_cppe5/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jmgrodriguez/main_hf_cppe5/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- e12709ab3a76c148571f5e6ab7d3c18a817892b842836641dcba86c7990b8a35
- Size of remote file:
- 5.3 kB
- SHA256:
- ca89f6027713de5f0d77485088a1658b57230d641c5f3da7413fc394cabc6160
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