Instructions to use TopKek/test2204_batch16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TopKek/test2204_batch16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="TopKek/test2204_batch16")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("TopKek/test2204_batch16") model = AutoModelForObjectDetection.from_pretrained("TopKek/test2204_batch16") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 97a2c4472e64bbe842d67ce3dc699a603f9af0097928018923f195942664db43
- Size of remote file:
- 167 MB
- SHA256:
- 9ccb536ff1521247bd0dfd4cef1409ff442a75b0c9f4de0d2e5a05bd92acceb9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.