Instructions to use limehee/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use limehee/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="limehee/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("limehee/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("limehee/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from limehee/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/limehee/cppe5_use_data_finetuning/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://limehee/cppe5_use_data_finetuning@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/limehee/cppe5_use_data_finetuning/resolve/refs%2Fpr%2F1/training_args.bin
4.54 kB
- Xet hash:
- 3c73181299c7f99eb45b461c5e9fd538a9db04f6e119cb509b972911c0e7e3f4
- Size of remote file:
- 4.54 kB
- SHA256:
- ca5196f36261cbc2701861321f753ab6b05eb73ca8c3fa6af4a1c36267e3a557
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