Instructions to use nvidia/groupvit-gcc-redcaps with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/groupvit-gcc-redcaps with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="nvidia/groupvit-gcc-redcaps")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("nvidia/groupvit-gcc-redcaps") model = AutoModel.from_pretrained("nvidia/groupvit-gcc-redcaps", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from nvidia/groupvit-gcc-redcaps: direct link, hf CLI and curl.
- Browser
- Download file 380 Bytes
-
https://huggingface.co/nvidia/groupvit-gcc-redcaps/resolve/refs%2Fpr%2F1/preprocessor_config.json
- Command line
-
hf download hf://nvidia/groupvit-gcc-redcaps@refs/pr/1/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/nvidia/groupvit-gcc-redcaps/resolve/refs%2Fpr%2F1/preprocessor_config.json
380 Bytes
| { | |
| "crop_size": 224, | |
| "do_center_crop": true, | |
| "do_convert_rgb": 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 | |
| ], | |
| "processor_class": "CLIPProcessor", | |
| "resample": 3, | |
| "size": 224 | |
| } | |