Instructions to use franciscomj0901/checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use franciscomj0901/checkpoints with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="franciscomj0901/checkpoints")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("franciscomj0901/checkpoints") model = AutoModelForObjectDetection.from_pretrained("franciscomj0901/checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e5f96642452bac2dc0d1f57281b732a627991b1b0928cd281cc1779279274a8d
- Size of remote file:
- 5.3 kB
- SHA256:
- a767ab334c208016901d9f9a933f13687511531a63babe5ea104cf68bae83fe4
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