Sentence Similarity
sentence-transformers
Safetensors
English
bert
task-oriented-dialogues
dialog-flow
text-embeddings-inference
Instructions to use sergioburdisso/dialog2flow-joint-bert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sergioburdisso/dialog2flow-joint-bert-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sergioburdisso/dialog2flow-joint-bert-base") sentences = [ "your phone please", "please get their phone number", "okay can i get your phone number please to make that booking", "okay can i please get your id number" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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- "That is a happy dog"
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- "That is a very happy person"
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- "Today is a sunny day"
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---
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- "That is a happy dog"
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- "That is a very happy person"
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- "Today is a sunny day"
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output:
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- label: "That is a happy dog"
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score: 0.853
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- label: "That is a very happy person"
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score: 0.981
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- label: "Today is a sunny day"
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score: 0.655
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