Image Segmentation
ultralytics
TensorBoard
PyTorch
v8
ultralyticsplus
yolov8
yolo
vision
Eval Results (legacy)
Instructions to use fcakyon/test-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use fcakyon/test-model 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("fcakyon/test-model", "<weights>.pt") model = YOLO(weights) source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Commit History
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Upload yolov8 tensorboard logs
d0d2c5c -
Upload yolov8 best model
a846cfa -
Delete events.out.tfevents.1673730246.DESKTOP-65UI233.15872.0 with huggingface_hub
0b72899 -
add ultralytics model card
b94ef7c -
upload sample visuals
421ca82 -
add ultralyticsplus config
2724509 -
Upload yolov8 tensorboard logs
1889976 -
Upload yolov8 best model
f51ee99 -
Delete events.out.tfevents.1673730246.DESKTOP-65UI233.15872.0 with huggingface_hub
ceaefa6 -
add ultralytics model card
b6908df -
upload sample visuals
d60c2ff -
add ultralyticsplus config
7547819 -
Upload yolov8 tensorboard logs
c0a0b69 -
Upload yolov8 best model
2c49bfb -
add ultralytics model card
b86f5d0 -
upload sample visuals
33a9baf -
add ultralyticsplus config
e4121b1 -
initial commit
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