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 config.json from Marqo/marqo-ecommerce-embeddings-L: direct link, hf CLI and curl.
- Browser
- Download file 310 Bytes
-
https://huggingface.co/Marqo/marqo-ecommerce-embeddings-L/resolve/main/config.json
- Command line
-
hf download hf://Marqo/marqo-ecommerce-embeddings-L/config.json
-
curl -L -o config.json https://huggingface.co/Marqo/marqo-ecommerce-embeddings-L/resolve/main/config.json
310 Bytes
| {"auto_map": {"AutoConfig": "marqo_fashionSigLIP.MarqoFashionSigLIPConfig", "AutoModel": "marqo_fashionSigLIP.MarqoFashionSigLIP", "AutoProcessor": "marqo_fashionSigLIP.MarqoFashionSigLIPProcessor"}, "open_clip_model_name": "hf-hub:Marqo/marqo-ecommerce-embeddings-L", "model_type": "siglip", "type": "siglip"} |