Sentence Similarity
sentence-transformers
Safetensors
Low German
xlm-roberta
trimmed
text-embeddings-inference
Instructions to use alphaedge-ai/multilingual-e5-large-instruct-nds-16384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use alphaedge-ai/multilingual-e5-large-instruct-nds-16384 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("alphaedge-ai/multilingual-e5-large-instruct-nds-16384") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 99e3b260e7e710620370b35bd11dfb60a550be6eb0a78a3f04573b3b240bb070
- Size of remote file:
- 641 MB
- SHA256:
- 5233269fb133d9693cafa093bee4bdc3a46a863b82e6c0ef0c66de954631471d
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