Instructions to use Xenova/yolos-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use Xenova/yolos-base with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('object-detection', 'Xenova/yolos-base');
Download preprocessor_config.json from Xenova/yolos-base: direct link, hf CLI and curl.
- Browser
- Download file 457 Bytes
-
https://huggingface.co/Xenova/yolos-base/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://Xenova/yolos-base/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/Xenova/yolos-base/resolve/main/preprocessor_config.json
457 Bytes
| { | |
| "do_normalize": true, | |
| "do_pad": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "feature_extractor_type": "YolosFeatureExtractor", | |
| "format": "coco_detection", | |
| "image_mean": [ | |
| 0.485, | |
| 0.456, | |
| 0.406 | |
| ], | |
| "image_processor_type": "YolosFeatureExtractor", | |
| "image_std": [ | |
| 0.229, | |
| 0.224, | |
| 0.225 | |
| ], | |
| "resample": 2, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "longest_edge": 1333, | |
| "shortest_edge": 800 | |
| } | |
| } | |