Instructions to use yeaool/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yeaool/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="yeaool/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("yeaool/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("yeaool/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from yeaool/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/yeaool/cppe5_use_data_finetuning/resolve/985adcd06da59c03f5b1ca916fa4ded59605c71a/pytorch_model.bin
- Command line
-
hf download hf://yeaool/cppe5_use_data_finetuning@985adcd06da59c03f5b1ca916fa4ded59605c71a/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/yeaool/cppe5_use_data_finetuning/resolve/985adcd06da59c03f5b1ca916fa4ded59605c71a/pytorch_model.bin
167 MB
- Xet hash:
- 6189e6a03b2b2586e2acaa8834f7353e1ae8699240131256cd2fbd62c69dc572
- Size of remote file:
- 167 MB
- SHA256:
- 7c11ea44b826709c223df2b47d714f9d5fcc7c6d1a06f9297594e44eb4d82577
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