Instructions to use han-byeol/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use han-byeol/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="han-byeol/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("han-byeol/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("han-byeol/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from han-byeol/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/han-byeol/cppe5_use_data_finetuning/resolve/45a4240e96ab36bfb43fbf07e348cd6088fc2f2f/pytorch_model.bin
- Command line
-
hf download hf://han-byeol/cppe5_use_data_finetuning@45a4240e96ab36bfb43fbf07e348cd6088fc2f2f/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/han-byeol/cppe5_use_data_finetuning/resolve/45a4240e96ab36bfb43fbf07e348cd6088fc2f2f/pytorch_model.bin
167 MB
- Xet hash:
- 6e37cac4368a784d609ac83fc055041ec05ace5d9b1fdadd94892d104e7183b5
- Size of remote file:
- 167 MB
- SHA256:
- f82c79a05e7d8a2f2de48849318e89557720689de57aeb7734fa433e1aa2e02d
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