Instructions to use panda47/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use panda47/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="panda47/cppe5_use_data_finetuning")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("panda47/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("panda47/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0185ad489d2083691ca2ba2adc4eac8ff60dd65d4c9e2b95cd84f9604064455d
- Size of remote file:
- 167 MB
- SHA256:
- 99d57e30deb851a410db11e3a78de97d7504b185d23c54d0e85ee41d223d39ed
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.