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Update model card: add zen/zenlm tags, fix branding

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  ---
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- library_name: transformers
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- pipeline_tag: feature-extraction
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  tags:
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- - embedding
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- - retrieval
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  - zen
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- - zen3
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  - hanzo
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- license: apache-2.0
 
 
 
 
 
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  ---
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- # Zen3 Embedding (OpenAI-compatible)
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- **Zen LM by Hanzo AI** — OpenAI-compatible embedding endpoint. Drop-in replacement for text-embedding-3-large.
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- ## Specs
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- | Property | Value |
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- |----------|-------|
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- | Parameters | API-served |
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- | Context | 8K |
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- | Architecture | Zen MoDE (Mixture of Distilled Experts) |
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- | Generation | Zen3 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## API Access
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- ```bash
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- curl https://api.hanzo.ai/v1/chat/completions \
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- -H "Authorization: Bearer $HANZO_API_KEY" \
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- -H "Content-Type: application/json" \
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- -d '{"model": "zen3-embedding-openai", "messages": [{"role": "user", "content": "Hello"}]}'
 
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  ```
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- Get your API key at [console.hanzo.ai](https://console.hanzo.ai) — $5 free credit on signup.
 
 
 
 
 
 
 
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  ## License
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  Apache 2.0
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-
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- ---
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-
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- *Zen LM is developed by [Hanzo AI](https://hanzo.ai) — Frontier AI infrastructure.*
 
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  ---
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+ language: en
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+ license: apache-2.0
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  tags:
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+ - feature-extraction
 
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  - zen
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+ - zenlm
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  - hanzo
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+ - zen3
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+ - embedding
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+ - retrieval
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+ - openai-compatible
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+ pipeline_tag: feature-extraction
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+ library_name: transformers
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  ---
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+ # Zen3 Embedding Openai
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+ OpenAI-API-compatible Zen3 embedding model for drop-in replacement of cloud embeddings.
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+ ## Overview
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+ Built on **Zen MoDE (Mixture of Distilled Experts)** architecture with medium parameters and 8K context window.
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+
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+ Developed by [Hanzo AI](https://hanzo.ai) and the [Zoo Labs Foundation](https://zoo.ngo).
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+
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+ ## Quick Start
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+
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+ ```python
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+ from sentence_transformers import SentenceTransformer
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+
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+ model = SentenceTransformer("zenlm/zen3-embedding-openai")
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+
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+ sentences = [
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+ "The weather is lovely today.",
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+ "It's so sunny outside!",
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+ "He drove to the stadium.",
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+ ]
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+ embeddings = model.encode(sentences)
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+ print(embeddings.shape)
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+
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+ # Compute cosine similarities
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+ similarities = model.similarity(embeddings, embeddings)
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+ print(similarities)
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+ ```
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  ## API Access
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+ ```python
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+ from openai import OpenAI
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+
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+ client = OpenAI(base_url="https://api.hanzo.ai/v1", api_key="your-api-key")
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+ response = client.embeddings.create(model="zen3-embedding-openai", input="Your text here")
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+ print(response.data[0].embedding)
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  ```
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+ ## Model Details
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+
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+ | Attribute | Value |
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+ |-----------|-------|
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+ | Parameters | medium |
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+ | Architecture | Zen MoDE |
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+ | Context | 8K tokens |
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+ | License | Apache 2.0 |
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  ## License
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  Apache 2.0