Document Embeddings
Based on the results of: https://arxiv.org/abs/2304.14796
Implemented Methods
- Average Pooling, with adjustable range for sentences used.
- PERT weighted average pooling
Usage
Wrapper for Sentence-Embedding, which is used to provide embedding functionality
from sentence_transformers import SentenceTransformer
sentence_model = SentenceTransformer("paraphrase-multilingual-MiniLM-L12-v2")
document_model = AverageDocumentEmbedding(sentence_model, language='german')
doc1 = "Arbitrary text"
doc2 = "..."
document_model.encode([doc1, doc2, ...])
Release files for document-embedding 0.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| document-embedding-0.0.1.tar.gz | 3.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| document_embedding-0.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 7.7 kB
Release files / document-embedding-0.0.1.tar.gz
| Download URL | document-embedding-0.0.1.tar.gz |
|---|---|
| Size | 3.9 kB |
| Tags | Source |
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Release files / document_embedding-0.0.1-py3-none-any.whl
| Download URL | document_embedding-0.0.1-py3-none-any.whl |
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| Size | 3.8 kB |
| Tags | Python 3 |
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