Sentence Similarity
sentence-transformers
BERTopic
English
topic-modeling
unsupervised-learning
document-clustering
document-archiving
human-in-the-loop
Instructions to use patpatrick/archivAI_document_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use patpatrick/archivAI_document_classification with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("patpatrick/archivAI_document_classification") 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] - BERTopic
How to use patpatrick/archivAI_document_classification with BERTopic:
from bertopic import BERTopic model = BERTopic.load("patpatrick/archivAI_document_classification") - Notebooks
- Google Colab
- Kaggle
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language:
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---
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language:
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- en
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base_model:
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- sentence-transformers/all-MiniLM-L6-v2
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pipeline_tag: sentence-similarity
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library_name: sentence-transformers
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tags:
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- bertopic
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- topic-modeling
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- unsupervised-learning
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- document-clustering
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- document-archiving
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- human-in-the-loop
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