Sentence Similarity
sentence-transformers
Safetensors
English
bert
bio-inspired
adapter
neural-architecture-search
neuroscience
feature-engineering
distillation
embeddings
semantic-search
sts
paraphrase-detection
clustering
Eval Results (legacy)
text-embeddings-inference
Instructions to use lakinekaki/all-MiniLM-L6-v2-genbais with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use lakinekaki/all-MiniLM-L6-v2-genbais with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("lakinekaki/all-MiniLM-L6-v2-genbais") 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] - Notebooks
- Google Colab
- Kaggle
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