Instructions to use yoon0915/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yoon0915/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="yoon0915/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("yoon0915/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("yoon0915/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from yoon0915/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/yoon0915/cppe5_use_data_finetuning/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://yoon0915/cppe5_use_data_finetuning/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/yoon0915/cppe5_use_data_finetuning/resolve/main/pytorch_model.bin
167 MB
- Xet hash:
- 173bbb5eaf13a96574adf0b4159fc1f874d30d1f61ffb7e7a2fa480db29cce68
- Size of remote file:
- 167 MB
- SHA256:
- 5b1d4153abbda03f9ab29bc7cd51601ecf473f51f596f28b5149c4f2bfa7af7b
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