Sentence Similarity
sentence-transformers
PyTorch
TensorFlow
Rust
ONNX
Safetensors
OpenVINO
English
bert
travel
recommendation
embeddings
text-embeddings-inference
Instructions to use avihayamor/tripmatch-ai-embedding-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use avihayamor/tripmatch-ai-embedding-model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("avihayamor/tripmatch-ai-embedding-model") 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
File size: 348 Bytes
25766ca | 1 2 3 4 5 | model_id,dimensions,encoding_seconds_10000,query_latency_ms,constraint_compatibility_at_3,embedding_file_mb,winner
sentence-transformers/all-MiniLM-L6-v2,384,41.683,1.052,0.8148,14.649,False
sentence-transformers/paraphrase-MiniLM-L3-v2,384,31.788,0.5,0.8194,14.649,True
sentence-transformers/all-MiniLM-L12-v2,384,84.478,1.463,0.8241,14.649,False
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