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:
- 933a51e1b96eba9f175a5e14663fbba6d26f33cad330ff31cf80ccfa482e5a7e
- Size of remote file:
- 5.88 MB
- SHA256:
- 40d814d559d55a4c8a7b7ff912024cd598e935c312914e3a9ab70677e32b3e0c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.