Feature Extraction
sentence-transformers
Safetensors
bert
retrieval
devdata-search
text-embeddings-inference
Instructions to use ai4data/devdata-search-multilingual-e5-small-cgist-guide-e5cmnrl 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-guide-e5cmnrl with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ai4data/devdata-search-multilingual-e5-small-cgist-guide-e5cmnrl") 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:
- f9edf108f52dfcf1d5fd56ade9e7315ba7cbad2cfed77bf6abbae4e86b78ba6e
- Size of remote file:
- 471 MB
- SHA256:
- d550eb7abec66d4eca1d3b227e67a4c2c9380e3eb567f5bfd2f62b1cb83f4a93
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.