NMF Embedding for Swarmauri.
Project description
NMF Embedding Package
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?
If you want to contribute to swarmauri-sdk, read up on our guidelines for contributing that will help you get started.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file swarmauri_embedding_nmf-0.6.1.dev15.tar.gz.
File metadata
- Download URL: swarmauri_embedding_nmf-0.6.1.dev15.tar.gz
- Upload date:
- Size: 6.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/2.1.1 CPython/3.12.9 Linux/6.8.0-1021-azure
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
c40002c9d8389041b8ab8e77de585ccbace4a4663a9743d99b959bc628ab6e12
|
|
| MD5 |
c8a78a5c5309e05092cbbea5187fdf33
|
|
| BLAKE2b-256 |
69f7ed5ac0f3fcd284c54ca44ebccbc5b36ac2af56b431bec4ada427d356f0ca
|
File details
Details for the file swarmauri_embedding_nmf-0.6.1.dev15-py3-none-any.whl.
File metadata
- Download URL: swarmauri_embedding_nmf-0.6.1.dev15-py3-none-any.whl
- Upload date:
- Size: 8.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/2.1.1 CPython/3.12.9 Linux/6.8.0-1021-azure
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
b2003a39d40f4efd13c8f05b8f9df39e422a5fe8b8e86b4c81e4b6fe4e6eb896
|
|
| MD5 |
2949281f116f8740ddd881281379a96c
|
|
| BLAKE2b-256 |
8190ce6785ba977ffec542a5c10669eb566d61a18e5b145ca63032bfba5d91b7
|