Push model using huggingface_hub.

README.md

@@ -1,39 +1,9 @@
 ---
-license: agpl-3.0
-pipeline_tag: object-detection
 tags:
-- ultralytics
-- yolo
-- yolov8
 - pytorch_model_hub_mixin
 - model_hub_mixin
 ---
 
-This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration.
-
-## Installation
-
-First install the package:
-
-```bash
-!pip install -q git+https://github.com/nielsrogge/ultralytics.git@feature/add_hf
-```
-
-## Usage
-
-YOLOv8 may also be used directly in a Python environment, and accepts the same [arguments](https://docs.ultralytics.com/usage/cfg/) as in the CLI:
-
-```python
-from ultralytics import YOLO
-
-# Load a model
-model = YOLO.from_pretrained("nielsr/yolov8n")
-
-# Use the model
-model.train(data="coco128.yaml", epochs=3)  # train the model
-metrics = model.val()  # evaluate model performance on the validation set
-results = model("https://ultralytics.com/images/bus.jpg")  # predict on an image
-path = model.export(format="onnx")  # export the model to ONNX format
-```
-
-See YOLOv8 [Python Docs](https://docs.ultralytics.com/usage/python) for more examples.
+This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
+- Library: [More Information Needed]
+- Docs: [More Information Needed]