ZeusMM

ZeusMM is a decoder-only multimodal conversational LM with:

• Role-aware RoPE + KV cache
• Dual fusion (Cross-Attn + FiLM) with a learned router
• Modality-aware MoE-MLP
• Drop-in vision (CLIP), audio (Wav2Vec2), retrieval (any HF encoder)

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer
repo = "Wonder-Griffin/ZeusMM"
tok = AutoTokenizer.from_pretrained(repo, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(repo, trust_remote_code=True)
prompt = "<|system|>You are Zeus.<|end|>\n<|user|>Say hi.<|end|>\n<|assistant|>"
x = tok(prompt, return_tensors="pt")
y = model.generate(**x, max_new_tokens=60, do_sample=True, top_p=0.9, temperature=0.9)
print(tok.decode(y[0], skip_special_tokens=False))



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## How to Get Started with the Model

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