Instructions to use SvNext/GambleStrTestYOLO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SvNext/GambleStrTestYOLO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="SvNext/GambleStrTestYOLO")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("SvNext/GambleStrTestYOLO") model = AutoModelForObjectDetection.from_pretrained("SvNext/GambleStrTestYOLO") - Notebooks
- Google Colab
- Kaggle
Upload YolosForObjectDetection
Browse files- config.json +4 -2
- pytorch_model.bin +2 -2
config.json
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"2": "LABEL_2",
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"3": "LABEL_3",
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"5": "LABEL_5"
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"image_size": [
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"LABEL_2": 2,
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"LABEL_5": 5
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"layer_norm_eps": 1e-12,
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"model_type": "yolos",
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"2": "LABEL_2",
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"3": "LABEL_3",
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"4": "LABEL_4",
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"5": "LABEL_5",
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"6": "LABEL_6"
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},
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"image_size": [
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800,
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"LABEL_2": 2,
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"LABEL_3": 3,
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"LABEL_4": 4,
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"LABEL_5": 5,
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"LABEL_6": 6
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"layer_norm_eps": 1e-12,
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"model_type": "yolos",
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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version https://git-lfs.github.com/spec/v1
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oid sha256:85b399ac398e7e3ffad378082ad065e2772b44eac9935961e1eead16cac80b2d
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size 25958678
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