| language: en | |
| license: apache-2.0 | |
| tags: | |
| - feature-extraction | |
| - zen | |
| - zenlm | |
| - hanzo | |
| - zen3 | |
| - embedding | |
| - retrieval | |
| pipeline_tag: feature-extraction | |
| library_name: transformers | |
| # Zen3 Embedding Medium | |
| Medium-sized Zen3 embedding model balancing speed and retrieval accuracy. | |
| ## Overview | |
| Built on **Zen MoDE (Mixture of Distilled Experts)** architecture with medium parameters and 8K context window. | |
| Developed by [Hanzo AI](https://hanzo.ai) and the [Zoo Labs Foundation](https://zoo.ngo). | |
| ## Quick Start | |
| ```python | |
| from sentence_transformers import SentenceTransformer | |
| model = SentenceTransformer("zenlm/zen3-embedding-medium") | |
| sentences = [ | |
| "The weather is lovely today.", | |
| "It's so sunny outside!", | |
| "He drove to the stadium.", | |
| ] | |
| embeddings = model.encode(sentences) | |
| print(embeddings.shape) | |
| # Compute cosine similarities | |
| similarities = model.similarity(embeddings, embeddings) | |
| print(similarities) | |
| ``` | |
| ## API Access | |
| ```python | |
| from openai import OpenAI | |
| client = OpenAI(base_url="https://api.hanzo.ai/v1", api_key="your-api-key") | |
| response = client.embeddings.create(model="zen3-embedding-medium", input="Your text here") | |
| print(response.data[0].embedding) | |
| ``` | |
| ## Model Details | |
| | Attribute | Value | | |
| |-----------|-------| | |
| | Parameters | medium | | |
| | Architecture | Zen MoDE | | |
| | Context | 8K tokens | | |
| | License | Apache 2.0 | | |
| ## License | |
| Apache 2.0 | |