Sentence Similarity
sentence-transformers
PyTorch
Safetensors
mpnet
feature-extraction
text-embeddings-inference
Instructions to use NASA-AIML/MIKA_Custom_IR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use NASA-AIML/MIKA_Custom_IR with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("NASA-AIML/MIKA_Custom_IR") sentences = [ "what components are vulnerable to fatigue crack?", "One of the first-stage compressor blades had fractued due to fatigue cracking.", "Witnesses and the fire department personnel noted fuel leaking due to a cracked fuel line.", "During periods of low visibility and night conditions, the supporting sensors sometimes conflict." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
File size: 349 Bytes
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{
"idx": 0,
"name": "0",
"path": "",
"type": "sentence_transformers.models.Transformer"
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{
"idx": 1,
"name": "1",
"path": "1_Pooling",
"type": "sentence_transformers.models.Pooling"
},
{
"idx": 2,
"name": "2",
"path": "2_Normalize",
"type": "sentence_transformers.models.Normalize"
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