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 ·
bb03bf1
1
Parent(s): 3ec547b
added pooling
Browse files- 1_Pooling/config.json +7 -0
1_Pooling/config.json
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{
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"word_embedding_dimension": 768,
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"pooling_mode_cls_token": false,
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"pooling_mode_mean_tokens": true,
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"pooling_mode_max_tokens": false,
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"pooling_mode_mean_sqrt_len_tokens": false
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}
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