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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9eac14dfffedec847a69f5f1c9ab5403973169a1be627aaa831bfcdfc294baf7
- Size of remote file:
- 2.24 GB
- SHA256:
- 0cf1883fee81c63819a44e2ba0efa51d4043d9759685a4ebebbde97e0623d15c
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