Instructions to use zerojun/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zerojun/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="zerojun/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("zerojun/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("zerojun/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from zerojun/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/zerojun/cppe5_use_data_finetuning/resolve/47a35f4f27792e22d2560b332a9670e1c7348e35/pytorch_model.bin
- Command line
-
hf download hf://zerojun/cppe5_use_data_finetuning@47a35f4f27792e22d2560b332a9670e1c7348e35/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/zerojun/cppe5_use_data_finetuning/resolve/47a35f4f27792e22d2560b332a9670e1c7348e35/pytorch_model.bin
167 MB
- Xet hash:
- 834942649dcf4445f51ae687faefcf97a4610bd1832f61539c14e25a72e40b84
- Size of remote file:
- 167 MB
- SHA256:
- c39abaf0b7304f9c907e9bf1fa00779425ec908d8c19a65a0ea1530f43afb1b6
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