Instructions to use gaf7921/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gaf7921/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="gaf7921/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("gaf7921/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("gaf7921/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from gaf7921/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/gaf7921/cppe5_use_data_finetuning/resolve/6cb071c1af2fdf7d316041459d6dbea3ec00e98d/pytorch_model.bin
- Command line
-
hf download hf://gaf7921/cppe5_use_data_finetuning@6cb071c1af2fdf7d316041459d6dbea3ec00e98d/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gaf7921/cppe5_use_data_finetuning/resolve/6cb071c1af2fdf7d316041459d6dbea3ec00e98d/pytorch_model.bin
167 MB
- Xet hash:
- 3e082ac4b7c4aad21423d2d8afcfe761a114dbe1b99acfb740f9239eb2ec8f22
- Size of remote file:
- 167 MB
- SHA256:
- fe9353954b73c79b803b9972b6ed46781718a1788f56e4a4db8282a7a9cfdb38
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