Instructions to use Moonjunho/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Moonjunho/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="Moonjunho/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("Moonjunho/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("Moonjunho/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Moonjunho/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/Moonjunho/cppe5_use_data_finetuning/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://Moonjunho/cppe5_use_data_finetuning@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Moonjunho/cppe5_use_data_finetuning/resolve/refs%2Fpr%2F1/training_args.bin
4.54 kB
- Xet hash:
- 9a1270a3a954591845f1d592263fc731da15efd10e2903b4979321b9e688d98e
- Size of remote file:
- 4.54 kB
- SHA256:
- ad6f74b18390bde3eb3ffc881717cfcd785a179d1fbc65b8d6083c18fee9ce2e
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