Instructions to use mmoz-root/kernelvision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use mmoz-root/kernelvision with ultralytics:
from ultralytics import YOLOvv8 model = YOLOvv8.from_pretrained("mmoz-root/kernelvision") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - TensorRT
How to use mmoz-root/kernelvision 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
| # Third-party notices | |
| KernelVision is an independent learning and benchmarking project. It is not | |
| affiliated with or endorsed by Ultralytics, NVIDIA, Modal, PyTorch, or OpenAI. | |
| ## Ultralytics YOLOv8 | |
| This project uses the Ultralytics Python package and the pretrained YOLOv8n | |
| model during reproduction and benchmarking. Ultralytics distributes its | |
| open-source software and model artifacts under the GNU Affero General Public | |
| License v3.0 (AGPL-3.0), subject to its published licensing terms: | |
| - <https://github.com/ultralytics/ultralytics> | |
| - <https://www.ultralytics.com/license> | |
| The Ultralytics Python package, original pretrained PyTorch checkpoint, and | |
| serialized TensorRT engines are not redistributed by KernelVision. | |
| Reproduction scripts obtain or consume them separately. The companion | |
| [Hugging Face model repository](https://huggingface.co/mmoz-root/kernelvision) | |
| publishes two derived ONNX graphs under AGPL-3.0 with explicit provenance and | |
| limitations. | |
| ## Ultralytics sample image | |
| The final annotated bus demonstration is derived from `bus.jpg`, accessed via | |
| the sample assets bundled with Ultralytics. The source asset repository is: | |
| - <https://github.com/ultralytics/assets> | |
| The annotated result is included only to document the benchmark output and | |
| remains subject to applicable upstream terms. | |
| ## Other dependencies | |
| KernelVision also depends on projects including PyTorch, Triton, ONNX, | |
| ONNX Runtime, TensorRT, OpenCV, NumPy, Matplotlib, and Modal. Each dependency | |
| is governed by its own license. Package version constraints are recorded in | |
| `pyproject.toml`, while exact benchmark versions are recorded in the result | |
| reports. | |
| NVIDIA, CUDA, TensorRT, and related names are trademarks or registered | |
| trademarks of NVIDIA Corporation. Other names may be trademarks of their | |
| respective owners. | |