Instructions to use PSW99/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PSW99/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="PSW99/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("PSW99/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("PSW99/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from PSW99/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/PSW99/cppe5_use_data_finetuning/resolve/731cd0f2df17d314c4e75aa697d2995fc03f668a/training_args.bin
- Command line
-
hf download hf://PSW99/cppe5_use_data_finetuning@731cd0f2df17d314c4e75aa697d2995fc03f668a/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/PSW99/cppe5_use_data_finetuning/resolve/731cd0f2df17d314c4e75aa697d2995fc03f668a/training_args.bin
4.54 kB
- Xet hash:
- 56d1158899f6bd430f17918cd552b4ace47e5d4d695783bc7434829312f46b40
- Size of remote file:
- 4.54 kB
- SHA256:
- dd6be23c7a1e616b136389f163f8c1db90dc249cac99a76320e65e1cc56cfd17
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.