Swarmauri Embedding Nmf
A Non-negative Matrix Factorization (NMF) based embedding implementation for text data processing in the Swarmauri ecosystem.
Installation
pip install swarmauri_embedding_nmf
Usage
Here's a basic example of how to use the NMF Embedding:
from swarmauri.embeddings.NmfEmbedding import NmfEmbedding
# Initialize the embedder
embedder = NmfEmbedding(n_components=10)
# Example documents
documents = ["This is the first document", "This is the second document", "And this is the third one"]
# Fit and transform the documents
vectors = embedder.fit_transform(documents)
# Transform a new document
new_vector = embedder.infer_vector("This is a new document")
Want to help?
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Metadata
Release files for swarmauri_embedding_nmf 0.7.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| swarmauri_embedding_nmf-0.7.5.tar.gz | 7.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| swarmauri_embedding_nmf-0.7.5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 15.1 kB
Release files / swarmauri_embedding_nmf-0.7.5.tar.gz
| Download URL | swarmauri_embedding_nmf-0.7.5.tar.gz |
|---|---|
| Size | 7.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Release files / swarmauri_embedding_nmf-0.7.5-py3-none-any.whl
| Download URL | swarmauri_embedding_nmf-0.7.5-py3-none-any.whl |
|---|---|
| Size | 8.0 kB |
| Tags | Python 3 |
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