Instructions to use ryul99/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ryul99/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="ryul99/cppe5_use_data_finetuning")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("ryul99/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("ryul99/cppe5_use_data_finetuning") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c4eb31d8a35d9351051aea5af7803c2ad3ec80c6101494a4cce6427a8d3a3039
- Size of remote file:
- 167 MB
- SHA256:
- 6273bc9e61fe7ae05b5fa991aab4a7f5d89fe647482fb09ce4becec5262a0330
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.