swarmauri_embedding_doc2vec 0.6.0

A Doc2Vec based Embedding Model.

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Doc2Vec Embedding

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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