Object Detection
ultralytics
ONNX
TensorRT
Vietnamese
yolo
yolov8
torchscript
int8
fp16
vision
traffic-sign
vietnam
Instructions to use liamxdev/vtsr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use liamxdev/vtsr with ultralytics:
from ultralytics import YOLOvv8 model = YOLOvv8.from_pretrained("liamxdev/vtsr") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - TensorRT
How to use liamxdev/vtsr with TensorRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 18faf3f2cfda2a870479e3f149e8647942e461418f5ce2c3d645710f684a215c
- Size of remote file:
- 6.43 MB
- SHA256:
- c69010d1f047c8e5906ede5122ebdd02950650e489906d6097f005d9c708212f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.