Instructions to use nonl/dfine-cppe5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nonl/dfine-cppe5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="nonl/dfine-cppe5")# Load model directly from transformers import AutoTokenizer, AutoModelForObjectDetection tokenizer = AutoTokenizer.from_pretrained("nonl/dfine-cppe5") model = AutoModelForObjectDetection.from_pretrained("nonl/dfine-cppe5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 886ab46b168a97d698f1e0bb3e22ecf8802bac5915653079de69e78fcc76e2be
- Size of remote file:
- 5.33 kB
- SHA256:
- ccbecee9773f9d27b7f82b4f4467786eaa20dc4fa13ef7d6df47594e8d2747e2
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