Instructions to use Marqo/marqo-ecommerce-embeddings-L with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- OpenCLIP
How to use Marqo/marqo-ecommerce-embeddings-L with OpenCLIP:
import open_clip model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms('hf-hub:Marqo/marqo-ecommerce-embeddings-L') tokenizer = open_clip.get_tokenizer('hf-hub:Marqo/marqo-ecommerce-embeddings-L') - Transformers
How to use Marqo/marqo-ecommerce-embeddings-L with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Marqo/marqo-ecommerce-embeddings-L", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from Marqo/marqo-ecommerce-embeddings-L: direct link, hf CLI and curl.
- Browser
- Download file 516 Bytes
-
https://huggingface.co/Marqo/marqo-ecommerce-embeddings-L/resolve/e5b81bfbd8064cc7397cd08f87bf79df76d60294/preprocessor_config.json
- Command line
-
hf download hf://Marqo/marqo-ecommerce-embeddings-L@e5b81bfbd8064cc7397cd08f87bf79df76d60294/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/Marqo/marqo-ecommerce-embeddings-L/resolve/e5b81bfbd8064cc7397cd08f87bf79df76d60294/preprocessor_config.json
516 Bytes
| { | |
| "auto_map": { | |
| "AutoProcessor": "marqo_fashionSigLIP.MarqoFashionSigLIPProcessor" | |
| }, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "do_convert_rgb": true, | |
| "image_processor_type": "SiglipImageProcessor", | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "processor_class": "marqo_fashionSigLIP.MarqoFashionSigLIPProcessor", | |
| "resample": 3, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "height": 224, | |
| "width": 224 | |
| }, | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ] | |
| } |