Instructions to use SpotLab/YOLOv8Detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SpotLab/YOLOv8Detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="SpotLab/YOLOv8Detection")# pip install -U transformers accelerate # Load model directly from transformers import Yolov8ForObjectDetection model = Yolov8ForObjectDetection.from_pretrained("SpotLab/YOLOv8Detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Properly name the architecture.
Jaime García Villena0e67cc0 -
Clean up keras generation files
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Revert "Export with nms"
Jaime García VillenaThis reverts commit 9bf782e2024e67e375f56d24bf75654f7fd2f8c0.a9623eb -
Export with nms
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move scripts and create README
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use new tflite model
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get the script to export
Jaime García Villena48730f0 -
add a way to test this tflite
Jaime García Villena7cd0692 -
fix(config): add model_type back, this time it's a YOLO
Jaime García Villena9684c94
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Correct detection tokens
Jaime García Villena151de84 -
Erase input size from config
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restore original name
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Add models and restore labels
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initial commit
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