zenlm/zen-vl-4b-instruct

Zen Vl 4b Instruct

Compact 4B vision-language model for image understanding and multimodal instruction following.

Overview

Built on Zen MoDE (Mixture of Distilled Experts) architecture with 4B parameters and 32K context window.

Developed by Hanzo AI and the Zoo Labs Foundation.

Quick Start

from transformers import AutoModelForVision2Seq, AutoProcessor
from PIL import Image
import torch

model_id = "zenlm/zen-vl-4b-instruct"
processor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForVision2Seq.from_pretrained(model_id, torch_dtype=torch.bfloat16, device_map="auto", trust_remote_code=True)

messages = [
    {"role": "user", "content": "Describe this image in detail."}
]

# Text-only
text = processor.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = processor(text=[text], return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=512)
print(processor.batch_decode(outputs, skip_special_tokens=True)[0])

API Access

from openai import OpenAI

client = OpenAI(base_url="https://api.hanzo.ai/v1", api_key="your-api-key")
response = client.chat.completions.create(
    model="zen-vl-4b-instruct",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)

Model Details

Attribute	Value
Parameters	4B
Architecture	Zen MoDE
Context	32K tokens
License	Apache 2.0

License

Apache 2.0