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:
- 5d9e8e6dc2dac440e6087a127e542ea9d113e484fa91b2f84c282204cd8f97b5
- Size of remote file:
- 3.58 kB
- SHA256:
- 454924e5a466d26026176c5acdb1d98ae8c1a2d2075b7f5a817acb7b1b04a961
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