Instructions to use hyo37009/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hyo37009/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="hyo37009/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("hyo37009/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("hyo37009/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hyo37009/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/hyo37009/cppe5_use_data_finetuning/resolve/d64f04dfd594191ec0fe95b6eded5abd72883a29/training_args.bin
- Command line
-
hf download hf://hyo37009/cppe5_use_data_finetuning@d64f04dfd594191ec0fe95b6eded5abd72883a29/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hyo37009/cppe5_use_data_finetuning/resolve/d64f04dfd594191ec0fe95b6eded5abd72883a29/training_args.bin
4.54 kB
- Xet hash:
- 59c0b251f807b1647241d1e0a421dcf97e4a37932ef78d544e9cc7be5e889c73
- Size of remote file:
- 4.54 kB
- SHA256:
- 24409902828930ba15b681432fee81ddb2d8d217f3363645ff01b5f7cf5da729
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