Object Detection
ultralytics
Safetensors
yolo
medical
tumor-detection
yolo11
brain tumor
computer vision
Eval Results (legacy)
Instructions to use LexBwmn/ACE-V1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use LexBwmn/ACE-V1 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("LexBwmn/ACE-V1", "<weights>.pt") model = YOLO(weights) source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Download results.png from LexBwmn/ACE-V1: direct link, hf CLI and curl.
- Browser
- Download file 145 kB
-
https://huggingface.co/LexBwmn/ACE-V1/resolve/main/results.png
- Command line
-
hf download hf://LexBwmn/ACE-V1/results.png
-
curl -L -o results.png https://huggingface.co/LexBwmn/ACE-V1/resolve/main/results.png
145 kB

- Xet hash:
- ea4f54ae83239be8ecc59db2472d02af8ff125d757e2384d208294f3cfd9e17f
- Size of remote file:
- 145 kB
- SHA256:
- 9324bad520821125b4f28156f3a5c1ce716cb45cd168cf94150c33dbfe954750
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