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 open_clip_model.safetensors from Marqo/marqo-ecommerce-embeddings-L: direct link, hf CLI and curl.
- Browser
- Download file 2.61 GB
-
https://huggingface.co/Marqo/marqo-ecommerce-embeddings-L/resolve/main/open_clip_model.safetensors
- Command line
-
hf download hf://Marqo/marqo-ecommerce-embeddings-L/open_clip_model.safetensors
-
curl -L -o open_clip_model.safetensors https://huggingface.co/Marqo/marqo-ecommerce-embeddings-L/resolve/main/open_clip_model.safetensors
2.61 GB
- Xet hash:
- b28724c6ecb768420b33904e43134ef22dbd598d2bc4f692d5520aa1ede22002
- Size of remote file:
- 2.61 GB
- SHA256:
- a586579224d119f10efb37d893970036654fb83653889953bb612dcbc8adf740
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