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:
- a326c5436d0db94ff05721b806b01fc6e509e7f67d1b268f8768eb490b2c81da
- Size of remote file:
- 41.1 MB
- SHA256:
- 5360724c24ab00d1a3073e73caa6f8c9abb13aa17c31dea30a11cf91823a9534
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