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
Commit ·
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Parent(s): 2a43df9
Update README.md
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README.md
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@@ -35,7 +35,7 @@ Then you can use the model like this:
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from sentence_transformers import SentenceTransformer
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sentences = ["This is an example sentence", "Each sentence is converted"]
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model = SentenceTransformer(
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embeddings = model.encode(sentences)
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print(embeddings)
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```
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from sentence_transformers import SentenceTransformer
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sentences = ["This is an example sentence", "Each sentence is converted"]
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model = SentenceTransformer("NASA-AIML/MIKA_Custom_IR")
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embeddings = model.encode(sentences)
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print(embeddings)
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```
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