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

README.md

@@ -1,55 +1,67 @@
 ---
-library_name: transformers
-pipeline_tag: feature-extraction
+language: en
+license: apache-2.0
 tags:
-  - embedding
-  - retrieval
-  - sentence-similarity
+  - feature-extraction
   - zen
-  - zen3
+  - zenlm
   - hanzo
-license: apache-2.0
+  - zen3
+  - embedding
+  - retrieval
+pipeline_tag: feature-extraction
+library_name: transformers
 ---
 
 # Zen3 Embedding Medium
 
-**Zen LM by Hanzo AI** — Text embedding model optimized for retrieval and similarity tasks. 335M parameters, 1024-dim embeddings.
+Medium-sized Zen3 embedding model balancing speed and retrieval accuracy.
+
+## Overview
 
-## Specs
+Built on **Zen MoDE (Mixture of Distilled Experts)** architecture with medium parameters and 8K context window.
 
-| Property | Value |
-|----------|-------|
-| Parameters | 335M |
-| Context Length | 512 tokens |
-| Dimensions | 1024 |
-| Architecture | Zen MoDE (Mixture of Distilled Experts) |
-| Generation | Zen3 |
+Developed by [Hanzo AI](https://hanzo.ai) and the [Zoo Labs Foundation](https://zoo.ngo).
 
-## Usage
+## Quick Start
 
 ```python
-from transformers import AutoModel, AutoTokenizer
+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)
 
-model = AutoModel.from_pretrained("zenlm/zen3-embedding-medium")
-tokenizer = AutoTokenizer.from_pretrained("zenlm/zen3-embedding-medium")
+# Compute cosine similarities
+similarities = model.similarity(embeddings, embeddings)
+print(similarities)
 ```
 
 ## API Access
 
-Available via the Hanzo AI API:
+```python
+from openai import OpenAI
 
-```bash
-curl https://api.hanzo.ai/v1/embeddings \
-  -H "Authorization: Bearer $HANZO_API_KEY" \
-  -d '{"model": "zen3-embedding-medium", "input": "Your text here"}'
+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)
 ```
 
-Get your API key at [console.hanzo.ai](https://console.hanzo.ai) — $5 free credit on signup.
+## Model Details
+
+| Attribute | Value |
+|-----------|-------|
+| Parameters | medium |
+| Architecture | Zen MoDE |
+| Context | 8K tokens |
+| License | Apache 2.0 |
 
 ## License
 
 Apache 2.0
-
----
-
-*Zen LM is developed by [Hanzo AI](https://hanzo.ai) — Frontier AI infrastructure.*