Instructions to use OrcaDB/clip-ViT-L-14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use OrcaDB/clip-ViT-L-14 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("OrcaDB/clip-ViT-L-14") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from OrcaDB/clip-ViT-L-14: direct link, hf CLI and curl.
- Browser
- Download file 504 Bytes
-
https://huggingface.co/OrcaDB/clip-ViT-L-14/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://OrcaDB/clip-ViT-L-14/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/OrcaDB/clip-ViT-L-14/resolve/main/preprocessor_config.json
504 Bytes
| { | |
| "crop_size": { | |
| "height": 224, | |
| "width": 224 | |
| }, | |
| "do_center_crop": true, | |
| "do_convert_rgb": true, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.48145466, | |
| 0.4578275, | |
| 0.40821073 | |
| ], | |
| "image_processor_type": "CLIPImageProcessor", | |
| "image_std": [ | |
| 0.26862954, | |
| 0.26130258, | |
| 0.27577711 | |
| ], | |
| "processor_class": "CLIPProcessor", | |
| "resample": 3, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "shortest_edge": 224 | |
| } | |
| } | |