Object Detection
ultralytics
PyTorch
Transformers
ONNX
Japanese
ultralyticsplus
yolov8
yolo
vision
image-segmentation
text-classification
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
README.md exists but content is empty.
- Downloads last month
- -