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miracle2568
/
ams

Object Detection
ultralytics
PyTorch
Transformers
ONNX
Japanese
ultralyticsplus
yolov8
yolo
vision
image-segmentation
text-classification
Model card Files Files and versions
xet
Community

Instructions to use miracle2568/ams with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • ultralytics

    How to use miracle2568/ams with ultralytics:

    from huggingface_hub import hf_hub_download
    from ultralytics import YOLO
    
    # pick the weights file from this repo's "Files and versions" tab
    weights = hf_hub_download("miracle2568/ams", "<weights>.pt")
    model = YOLO(weights)
    source = 'http://images.cocodataset.org/val2017/000000039769.jpg'
    model.predict(source=source, save=True)
  • Transformers

    How to use miracle2568/ams with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("object-detection", model="miracle2568/ams")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("miracle2568/ams", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
ams
1.8 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 5 commits
miracle2568's picture
miracle2568
Update README.md
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  • README.md
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    Update README.md almost 3 years ago