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/a206ee9cb32c2df1afca5c36b453d5a55356e39a/pytorch_model.bin
- Command line
-
hf download hf://yeaool/cppe5_use_data_finetuning@a206ee9cb32c2df1afca5c36b453d5a55356e39a/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/yeaool/cppe5_use_data_finetuning/resolve/a206ee9cb32c2df1afca5c36b453d5a55356e39a/pytorch_model.bin
167 MB
- Xet hash:
- bbf198143de1fab3e2e78ffa3704eb076dc745ca509cfe7beb5abf71c739f5ee
- Size of remote file:
- 167 MB
- SHA256:
- 5d71100259382953bb122169553ec4f7f1c40e1ccb06f12ce162065ebed29d04
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