Instructions to use Qdrant/multilingual-e5-large-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Qdrant/multilingual-e5-large-onnx with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Qdrant/multilingual-e5-large-onnx") model = AutoModel.from_pretrained("Qdrant/multilingual-e5-large-onnx", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 29c4d389726900c7c3bb3a7ffa57c4f2bfccac0a36fe33ca9726963526b1b962
- Size of remote file:
- 546 kB
- SHA256:
- 1c09780c907c8a91a77a6ab1fd231f79e090d2907ca431223703dfebeed3d36c
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