Instructions to use builtinnya/bsr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use builtinnya/bsr 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("builtinnya/bsr", "<weights>.pt") model = YOLO(weights) source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Download config.json from builtinnya/bsr: direct link, hf CLI and curl.
- Browser
- Download file 554 Bytes
-
https://huggingface.co/builtinnya/bsr/resolve/main/config.json
- Command line
-
hf download hf://builtinnya/bsr/config.json
-
curl -L -o config.json https://huggingface.co/builtinnya/bsr/resolve/main/config.json
554 Bytes
| { | |
| "input_size": 640, | |
| "architectures": [ | |
| "YolosForObjectDetection" | |
| ], | |
| "task": "object-detection", | |
| "model_type": "yolosv8", | |
| "id2label": { | |
| "0": "shotgun", | |
| "1": "live_round", | |
| "2": "blank_round", | |
| "3": "dealer_text", | |
| "4": "you_text", | |
| "5": "charge", | |
| "6": "magnifying_glass", | |
| "7": "cigarette_pack", | |
| "8": "beer_can", | |
| "9": "folding_saw", | |
| "10": "handcuffs", | |
| "11": "burner_phone", | |
| "12": "inverter", | |
| "13": "expired_medicine", | |
| "14": "adrenaline_shot" | |
| }, | |
| "transformers_version": "4.44.0" | |
| } |