Sentence Similarity
sentence-transformers
Safetensors
Western Frisian
xlm-roberta
trimmed
text-embeddings-inference
Instructions to use alphaedge-ai/multilingual-e5-base-fry-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-base-fry-16384 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("alphaedge-ai/multilingual-e5-base-fry-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:
- abe4d79b42b47a9e86a7fcb97e0d9fd52ce68d68aee522794ec12918ebccfeeb
- Size of remote file:
- 395 MB
- SHA256:
- af8ae585026a5e3d4f5b08bf0a7d3cde6ea394675585a49f3ac58cfa157256cd
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