Instructions to use sys2/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sys2/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="sys2/cppe5_use_data_finetuning")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("sys2/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("sys2/cppe5_use_data_finetuning") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0e930e9c825c5268d4d7d2eb60edc78af8f6fe65366bbeb2b0e7579a5d21ac06
- Size of remote file:
- 166 MB
- SHA256:
- f45c5a1bae8abb62207be178e2968c899409087facb43919b0057e8e0d069bd1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.