Instructions to use zenlm/zen3-omni with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use zenlm/zen3-omni with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="zenlm/zen3-omni")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("zenlm/zen3-omni")
model = AutoModelForMultimodalLM.from_pretrained("zenlm/zen3-omni", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = processor.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use zenlm/zen3-omni with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "zenlm/zen3-omni"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "zenlm/zen3-omni",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/zenlm/zen3-omni

SGLang

How to use zenlm/zen3-omni with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "zenlm/zen3-omni" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "zenlm/zen3-omni",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "zenlm/zen3-omni" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "zenlm/zen3-omni",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use zenlm/zen3-omni with Docker Model Runner:
```
docker model run hf.co/zenlm/zen3-omni
```

zeekay commited on Feb 24

Commit

bbf5566

verified ·

1 Parent(s): 7bfcee7

Update Zen3 Omni model card

Browse files

Files changed (1) hide show

README.md +37 -21

README.md CHANGED Viewed

@@ -1,27 +1,43 @@
 ---
 library_name: transformers
-tags: [zen, multimodal, vision, audio, hanzo]
 license: apache-2.0
 ---
-# Zen3 Omni — Hypermodal
-Multimodal model supporting text, vision, audio, and structured output.
-- **Developer**: [Hanzo AI](https://hanzo.ai) × [Zen LM](https://zenlm.org)
-- **Parameters**: ~200B
-- **Architecture**: Dense Multimodal
-- **Context**: 202K tokens
-- **Modalities**: Text + Vision + Audio
-- **API**: [api.hanzo.ai](https://cloud.hanzo.ai)
-- **Docs**: [zenlm.org/docs/models/zen3-omni](https://zenlm.org/docs/models/zen3-omni)
-## Usage
-```python
-from hanzo import Hanzo
-client = Hanzo()
-response = client.chat.completions.create(model="zen3-omni", messages=[{"role": "user", "content": "Describe this image"}])
 ```
-## Related
-- [zen-omni](https://huggingface.co/zenlm/zen-omni) — Base weights
-- [zen-omni-30b-instruct](https://huggingface.co/zenlm/zen-omni-30b-instruct) — Instruction-tuned

 ---
 library_name: transformers
+pipeline_tag: text-generation
+tags:
+  - text-generation
+  - multimodal
+  - zen
+  - zen3
+  - hanzo
 license: apache-2.0
 ---
+# Zen3 Omni
+**Zen LM by Hanzo AI** — Multimodal model supporting text, vision, and audio in a single architecture.
+## Specs
+| Property | Value |
+|----------|-------|
+| Parameters | 4.7B Dense |
+| Context | 202K |
+| Architecture | Zen MoDE (Mixture of Distilled Experts) |
+| Generation | Zen3 |
+## API Access
+```bash
+curl https://api.hanzo.ai/v1/chat/completions \
+  -H "Authorization: Bearer $HANZO_API_KEY" \
+  -H "Content-Type: application/json" \
+  -d '{"model": "zen3-omni", "messages": [{"role": "user", "content": "Hello"}]}'
 ```
+Get your API key at [console.hanzo.ai](https://console.hanzo.ai) — $5 free credit on signup.
+## License
+Apache 2.0
+---
+*Zen LM is developed by [Hanzo AI](https://hanzo.ai) — Frontier AI infrastructure.*