Zen Omni 30B Thinking
Advanced multimodal model with thinking and audio capabilities from the Zen family.
Model Details
- Architecture: Qwen2-based with multimodal extensions
- Parameters: 31.7B
- Context Length: 32,768 tokens
- Modalities: Text, Audio, Thinking
- Hidden Size: 5,120
- Layers: 64
- Attention Heads: 40
- Developer: Hanzo AI
Features
- Thinking Module: Chain-of-thought reasoning capabilities
- Audio Tower: Audio processing and understanding
- Multimodal Integration: Seamless text and audio processing
Usage
PyTorch
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("zenlm/zen-omni-30b-thinking")
tokenizer = AutoTokenizer.from_pretrained("zenlm/zen-omni-30b-thinking")
# Generate text
prompt = "Explain quantum computing"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=100)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response)
Available Formats
- PyTorch: Default safetensors format (16 shards)
- GGUF: Coming soon
- MLX: Coming soon
Hardware Requirements
- VRAM: ~64GB for full precision
- RAM: 128GB recommended
- Storage: ~60GB for model files
Training
Fine-tuned with:
- Zen identity
- Multimodal understanding
- Chain-of-thought reasoning
- Audio processing capabilities
Model Components
thinker.*
: Thinking/reasoning moduleaudio_tower.*
: Audio processing layers- Standard transformer layers for text generation
License
Apache 2.0
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