Instructions to use PekingU/rtdetr_r101vd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PekingU/rtdetr_r101vd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="PekingU/rtdetr_r101vd")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("PekingU/rtdetr_r101vd") model = AutoModelForObjectDetection.from_pretrained("PekingU/rtdetr_r101vd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update config.json (#1)
Browse files- Update config.json (e4cb88bfcb8d8c0309e5108ef9d6425f393eda5f)
Co-authored-by: Pavel Iakubovskii <qubvel-hf@users.noreply.huggingface.co>
- config.json +1 -4
config.json
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{
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"activation_dropout": 0.0,
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"activation_function": "silu",
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"anchor_image_size":
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640,
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640
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],
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"architectures": [
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"RTDetrForObjectDetection"
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],
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{
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"activation_dropout": 0.0,
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"activation_function": "silu",
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"anchor_image_size": null,
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"architectures": [
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"RTDetrForObjectDetection"
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],
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