Zen3 Embedding Openai

OpenAI-API-compatible Zen3 embedding model for drop-in replacement of cloud embeddings.

Overview

Built on Zen MoDE (Mixture of Distilled Experts) architecture with medium parameters and 8K context window.

Developed by Hanzo AI and the Zoo Labs Foundation.

Quick Start

from sentence_transformers import SentenceTransformer

model = SentenceTransformer("zenlm/zen3-embedding-openai")

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

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-openai", 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

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Safetensors
Model size
0.6B params
Tensor type
BF16
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