Swarmauri Embedding Doc2vec
A Gensim-based Doc2Vec implementation for document embedding in the Swarmauri ecosystem. This package provides document vectorization capabilities using the Doc2Vec algorithm.
Installation
pip install swarmauri_embedding_doc2vec
Usage
from swarmauri.embeddings.Doc2VecEmbedding import Doc2VecEmbedding
# Initialize the embedder
embedder = Doc2VecEmbedding(vector_size=3000)
# Prepare your documents
documents = ["This is the first document.", "Here is another document.", "And a third one"]
# Fit and transform documents
vectors = embedder.fit_transform(documents)
# Transform new documents
new_doc = "This is a new document"
vector = embedder.transform([new_doc])
# Save and load the model
embedder.save_model("doc2vec.model")
embedder.load_model("doc2vec.model")
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Metadata
1 maintainer
Release files for swarmauri_embedding_doc2vec 0.7.5
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Source distribution (sdist)
| File | Size | Uploaded | |
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| swarmauri_embedding_doc2vec-0.7.5.tar.gz | 7.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| swarmauri_embedding_doc2vec-0.7.5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 15.0 kB
Release files / swarmauri_embedding_doc2vec-0.7.5.tar.gz
| Download URL | swarmauri_embedding_doc2vec-0.7.5.tar.gz |
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| Size | 7.0 kB |
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Release files / swarmauri_embedding_doc2vec-0.7.5-py3-none-any.whl
| Download URL | swarmauri_embedding_doc2vec-0.7.5-py3-none-any.whl |
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| Size | 8.0 kB |
| Tags | Python 3 |
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