Instructions to use PCFISH/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PCFISH/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="PCFISH/cppe5_use_data_finetuning")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("PCFISH/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("PCFISH/cppe5_use_data_finetuning") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 85eda83736aed07a5b8d2c03495bedd914b2a76112806a46fd1c28837c13aa1b
- Size of remote file:
- 167 MB
- SHA256:
- 6e664ade2eeee56e82d8203b494c7ec7b28e9eac66d5dfde22860d0ddd854cd6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.