Instructions to use nyoo827/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nyoo827/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="nyoo827/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("nyoo827/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("nyoo827/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from nyoo827/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/nyoo827/cppe5_use_data_finetuning/resolve/2bbd418c8b93bcd96b7cbcdb65ef0adec8dfef67/pytorch_model.bin
- Command line
-
hf download hf://nyoo827/cppe5_use_data_finetuning@2bbd418c8b93bcd96b7cbcdb65ef0adec8dfef67/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/nyoo827/cppe5_use_data_finetuning/resolve/2bbd418c8b93bcd96b7cbcdb65ef0adec8dfef67/pytorch_model.bin
167 MB
- Xet hash:
- 314b594506bac270f9e0bb1eff4c161c8a1934918a20d4c32234b6529d142ef7
- Size of remote file:
- 167 MB
- SHA256:
- 22f1a849c0a68f29d4e8ef8ab5fee1caf8ac534f6ec396a56768f3faa917a3f5
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