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Venera-Tiny-Embedding-Model
venustar/Venera-Tiny-Embedding-Model
Venera-Tiny-Embedding-Model is a machine learning model from venustar. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
A lightweight text embedding model created for experimentation, demos, and simple NLP pipelines. Designed to transform sentences into fixed-size vectors for similarity search, clustering, and retrieval tasks.
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Updated Dec 10, 2025
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At a glance
- Access
- Public
- Created
- Dec 10, 2025
- Updated
- Dec 10, 2025
- SHA
- d8e2cb87
Model card
From the Hugging Face model README
Venera Tiny Embedding Model
A lightweight text embedding model created for experimentation, demos, and simple NLP pipelines.
Designed to transform sentences into fixed-size vectors for similarity search, clustering, and retrieval tasks.
Key Features
- Ultra-lightweight (demo-friendly)
- Fast inference on CPU
- Great for prototypes and student projects
- Ideal for learning how to host models on Hugging Face
Example Usage
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("your-username/venera-tiny-embed")
emb = model.encode("Hello Venera")
print(emb)
- Created
- Dec 10, 2025
- Updated
- Dec 10, 2025