Feature Extraction
sentence-transformers
Safetensors
bert
retrieval
devdata-search
text-embeddings-inference
Instructions to use ai4data/devdata-search-multilingual-e5-small-cgist with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ai4data/devdata-search-multilingual-e5-small-cgist with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ai4data/devdata-search-multilingual-e5-small-cgist") 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:
- aebb1d7f84383faa6c6d81251f46b63d5487d4c247bf4aa39252b870945f92ff
- Size of remote file:
- 471 MB
- SHA256:
- e335d16a3baf04fa1d9e417f2642451a4355b2c97fc01927f885e71ff0d3a50a
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