Instructions to use q-future/Compare2Score with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use q-future/Compare2Score with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="q-future/Compare2Score", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("q-future/Compare2Score", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from q-future/Compare2Score: direct link, hf CLI and curl.
- Browser
- Download file 317 Bytes
-
https://huggingface.co/q-future/Compare2Score/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://q-future/Compare2Score/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/q-future/Compare2Score/resolve/main/preprocessor_config.json
317 Bytes
| { | |
| "crop_size": 448, | |
| "do_center_crop": true, | |
| "do_normalize": true, | |
| "do_resize": true, | |
| "feature_extractor_type": "CLIPFeatureExtractor", | |
| "image_mean": [ | |
| 0.48145466, | |
| 0.4578275, | |
| 0.40821073 | |
| ], | |
| "image_std": [ | |
| 0.26862954, | |
| 0.26130258, | |
| 0.27577711 | |
| ], | |
| "resample": 3, | |
| "size": 448 | |
| } | |