Sentence Similarity
sentence-transformers
PyTorch
TensorFlow
ONNX
Safetensors
OpenVINO
distilbert
feature-extraction
text-embeddings-inference
Instructions to use sentence-transformers/distiluse-base-multilingual-cased-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sentence-transformers/distiluse-base-multilingual-cased-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sentence-transformers/distiluse-base-multilingual-cased-v1") 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] - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from sentence-transformers/distiluse-base-multilingual-cased-v1: direct link, hf CLI and curl.
- Browser
- Download file 539 MB
-
https://huggingface.co/sentence-transformers/distiluse-base-multilingual-cased-v1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://sentence-transformers/distiluse-base-multilingual-cased-v1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sentence-transformers/distiluse-base-multilingual-cased-v1/resolve/main/pytorch_model.bin
539 MB
- Xet hash:
- 5c1ccbfa83772f75b160ec3a2367019bda33794fce9cef67932519d74d62b54c
- Size of remote file:
- 539 MB
- SHA256:
- 03df542359d538498eb007919af1b80d555135257b26e0777b96bfce9ecde138
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