Instructions to use mrsarthakgupta/openclipvisionmodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrsarthakgupta/openclipvisionmodel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="mrsarthakgupta/openclipvisionmodel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("mrsarthakgupta/openclipvisionmodel") model = AutoModel.from_pretrained("mrsarthakgupta/openclipvisionmodel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from mrsarthakgupta/openclipvisionmodel: direct link, hf CLI and curl.
- Browser
- Download file 371 Bytes
-
https://huggingface.co/mrsarthakgupta/openclipvisionmodel/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://mrsarthakgupta/openclipvisionmodel/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/mrsarthakgupta/openclipvisionmodel/resolve/main/preprocessor_config.json
371 Bytes
| { | |
| "crop_size": 224, | |
| "do_center_crop": true, | |
| "do_normalize": true, | |
| "do_resize": true, | |
| "feature_extractor_type": "CLIPFeatureExtractor", | |
| "model_type": "clip_vision_model", | |
| "image_mean": [ | |
| 0.48145466, | |
| 0.4578275, | |
| 0.40821073 | |
| ], | |
| "image_std": [ | |
| 0.26862954, | |
| 0.26130258, | |
| 0.27577711 | |
| ], | |
| "resample": 3, | |
| "size": 224 | |
| } |