TF-IDF Embedding
A TF-IDF (Term Frequency-Inverse Document Frequency) embedding implementation for the Swarmauri SDK, providing document vectorization capabilities.
Installation
pip install swarmauri_embedding_tfidf
Usage
from swarmauri_embedding_tfidf.TfidfEmbedding import TfidfEmbedding
# Initialize the embedder
embedder = TfidfEmbedding()
# Prepare documents
documents = ["this is a sample", "another example text", "third document here"]
# Fit and transform documents
vectors = embedder.fit_transform(documents)
# Infer vector for new text
query_vector = embedder.infer_vector("new document", documents)
# Extract features
features = embedder.extract_features()
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Metadata
Release files for swarmauri_embedding_tfidf 0.6.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| swarmauri_embedding_tfidf-0.6.1.tar.gz | 6.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| swarmauri_embedding_tfidf-0.6.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 14.1 kB
Release files / swarmauri_embedding_tfidf-0.6.1.tar.gz
| Download URL | swarmauri_embedding_tfidf-0.6.1.tar.gz |
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| Size | 6.5 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Release files / swarmauri_embedding_tfidf-0.6.1-py3-none-any.whl
| Download URL | swarmauri_embedding_tfidf-0.6.1-py3-none-any.whl |
|---|---|
| Size | 7.6 kB |
| Tags | Python 3 |
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