Instructions to use yunnn426/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yunnn426/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="yunnn426/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("yunnn426/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("yunnn426/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from yunnn426/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/yunnn426/cppe5_use_data_finetuning/resolve/main/training_args.bin
- Command line
-
hf download hf://yunnn426/cppe5_use_data_finetuning/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/yunnn426/cppe5_use_data_finetuning/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- 375a8fa34cc28cf7a49e99ea93785d959f4e96e67489f31041694c49ba51abf7
- Size of remote file:
- 4.54 kB
- SHA256:
- 2085d1c725cac5bcd6e9610b0e65b9c7bfe268feb08b3f3cbe57b2aa71b289cf
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