Instructions to use SvNext/GambleTestDETR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SvNext/GambleTestDETR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="SvNext/GambleTestDETR")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("SvNext/GambleTestDETR") model = AutoModelForObjectDetection.from_pretrained("SvNext/GambleTestDETR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload DetrForObjectDetection
Browse files- config.json +2 -8
- pytorch_model.bin +2 -2
config.json
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"giou_cost": 2,
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"giou_loss_coefficient": 2,
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"id2label": {
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"0": "LABEL_0"
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"1": "LABEL_1",
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"2": "LABEL_2",
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"3": "LABEL_3"
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"init_std": 0.02,
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"init_xavier_std": 1.0,
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"is_encoder_decoder": true,
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"label2id": {
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"LABEL_0": 0
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"LABEL_3": 3
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"mask_loss_coefficient": 1,
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"model_type": "detr",
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"giou_cost": 2,
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"giou_loss_coefficient": 2,
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"id2label": {
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"0": "LABEL_0"
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},
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"init_std": 0.02,
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"init_xavier_std": 1.0,
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"is_encoder_decoder": true,
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"label2id": {
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"LABEL_0": 0
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"mask_loss_coefficient": 1,
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"model_type": "detr",
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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size
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version https://git-lfs.github.com/spec/v1
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size 166616594
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