Sentence Similarity
sentence-transformers
PyTorch
TensorFlow
ONNX
Safetensors
OpenVINO
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use sentence-transformers/paraphrase-MiniLM-L6-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sentence-transformers/paraphrase-MiniLM-L6-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sentence-transformers/paraphrase-MiniLM-L6-v2") 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/paraphrase-MiniLM-L6-v2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sentence-transformers/paraphrase-MiniLM-L6-v2") model = AutoModel.from_pretrained("sentence-transformers/paraphrase-MiniLM-L6-v2") - Inference
- Notebooks
- Google Colab
- Kaggle
Using the model locally
1
#9 opened almost 2 years ago
by
KaustubhRatna
Training Data
#6 opened over 2 years ago
by
WR-FS
How do I reduce the size of sentence-transformers?
1
#5 opened over 2 years ago
by
deejaypepe
Deployment on Amazon Sagemaker
#3 opened almost 4 years ago
by
ygrajashree
Training dataset confirmation
2
#2 opened almost 4 years ago
by
CShorten