Sentence Similarity
sentence-transformers
PyTorch
TensorFlow
ONNX
Safetensors
OpenVINO
Transformers
English
bert
feature-extraction
text-embeddings-inference
Instructions to use sentence-transformers/multi-qa-MiniLM-L6-dot-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sentence-transformers/multi-qa-MiniLM-L6-dot-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sentence-transformers/multi-qa-MiniLM-L6-dot-v1") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use sentence-transformers/multi-qa-MiniLM-L6-dot-v1 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sentence-transformers/multi-qa-MiniLM-L6-dot-v1") model = AutoModel.from_pretrained("sentence-transformers/multi-qa-MiniLM-L6-dot-v1") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
Add new SentenceTransformer model with an openvino backend aae9b50 verified
Add new SentenceTransformer model with an openvino backend bf5f138 verified
Add exported ONNX model 'model_qint8_avx512_vnni.onnx' b4ef855 verified
Add exported ONNX model 'model_qint8_avx512.onnx' 272825f verified
Add exported ONNX model 'model_quint8_avx2.onnx' 363681c verified
Add exported ONNX model 'model_qint8_arm64.onnx' cf360db verified
Add exported ONNX model 'model_O4.onnx' 4c8d798 verified
Add exported ONNX model 'model_O3.onnx' 7aaed50 verified
Add exported ONNX model 'model_O2.onnx' 16882e2 verified
Add exported ONNX model 'model_O1.onnx' 6ca5406 verified
Add new SentenceTransformer model with an onnx backend 4b9e865 verified
Add "dot" similarity function c3bdeb0 verified
Add TF weights cffdcf0
Joao Gante commited on