Instructions to use gaf7921/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gaf7921/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="gaf7921/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("gaf7921/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("gaf7921/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from gaf7921/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/gaf7921/cppe5_use_data_finetuning/resolve/main/training_args.bin
- Command line
-
hf download hf://gaf7921/cppe5_use_data_finetuning/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/gaf7921/cppe5_use_data_finetuning/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- 8279b48463954bbee9f6a31f6dde7a59cd422c9bc9e5497ed03532aa6ffa48be
- Size of remote file:
- 4.54 kB
- SHA256:
- 97ba4b364b07e619e0fd1d1640398d9bd699f93d543d0b1bb91fc04511e0317f
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