🧠 ZeroXClem/Qwen3-4B-MiniMight

MiniMight

"Small in scale. Mighty in mind."
A beautifully blended 4B model with 262k context length, fusing deep reasoning, code, safety, and creativity β€” distilled through MergeKit’s model_stock magic.


πŸ”§ Merge Configuration

name: ZeroXClem/Qwen3-4B-MiniMight
base_model: Qwen/Qwen3-4B-Thinking-2507
dtype: bfloat16
merge_method: model_stock
models:
  - model: TeichAI/Qwen3-4B-Thinking-2507-Claude-4.5-Opus-High-Reasoning-Distill
  - model: bunnycore/Qwen3-4B-Mini-Merge
  - model: bunnycore/Qwen3-4B-MegaMerge
  - model: bunnycore/Qwen3-4B-Max-Merge
  - model: ertghiu256/qwen3-4b-claude-sonnet-x-gemini-reasoning
  - model: ZeroXClem/Qwen3-4B-Hermes-Axion-Pro
tokenizer_source: Qwen/Qwen3-4B-Thinking-2507

🌟 Highlights

  • 🧠 Reasoning-Centric Intelligence β€” Optimized for multi-step thought, explanation, STEM logic, and symbolic problem solving.
  • πŸͺ 262,144 Token Context Window β€” Massive memory span for long documents, complex chains, or multi-turn workflows.
  • 🧬 Deep Merge of Code, RP, and Claude/Gemini Logic β€” Captures both fluency and fidelity in multi-domain generation.
  • πŸ” Safe Alignment from Hermes & Axion β€” Includes red-teamed safety-conscious merges to guide outputs.
  • ✍️ Elegant Dialogue & Creative Thought β€” Engages in immersive roleplay, structured writing, and storytelling.
  • ⚑ Efficient 4B Inference β€” Small enough for local GPUs, quantized formats, and mobile deployments.

πŸ§ͺ Usage Example

from transformers import AutoTokenizer, AutoModelForCausalLM

model = AutoModelForCausalLM.from_pretrained("ZeroXClem/Qwen3-4B-MiniMight", device_map="auto", torch_dtype="auto")
tokenizer = AutoTokenizer.from_pretrained("ZeroXClem/Qwen3-4B-MiniMight")

messages = [{"role": "user", "content": "Explain quantum tunneling with an example."}]
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)

inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=384)

print(tokenizer.decode(outputs[0], skip_special_tokens=True))

🧠 Use enable_thinking=True or /think with compatible frontends for enhanced reasoning control.


πŸ” Models Merged

Source Model Specialization
TeichAI/Qwen3-4B-Thinking-2507-Claude-4.5-Opus-High-Reasoning-Distill High reasoning distilled from Claude Opus
bunnycore/Qwen3-4B-Mini-Merge Mini-coder, Qwaifu, Darwin blend
bunnycore/Qwen3-4B-MegaMerge AesCoder + OSS GPT + Qwaifu fusion
bunnycore/Qwen3-4B-Max-Merge Maximal blend with strong instruction coherence
ertghiu256/qwen3-4b-claude-sonnet-x-gemini-reasoning Gemini 3 Pro & Claude Sonnet enhanced
ZeroXClem/Qwen3-4B-Hermes-Axion-Pro Reasoning + alignment + safety-core logic

πŸ’Ό Ideal For

  • πŸ” Chain-of-thought reasoning & symbolic logic
  • πŸ§ͺ Long-document summarization & analysis
  • πŸ’¬ Roleplay & storytelling with high memory
  • πŸ“š Tutoring & educational AI (math, code, science)
  • βš–οΈ Safety-aligned assistants for deployment
  • πŸ‘¨β€πŸ’» Code generation, refactoring, and walkthroughs

🚫 Limitations

  • Long responses may truncate if max_new_tokens is too low
  • Mixed training sources may result in style variance across domains
  • Dialogue tone defaults to helpful/instructive rather than emotional/creative

πŸ“œ License

Apache 2.0 Please verify license alignment when adapting for commercial or public-facing use.


πŸ’Œ Credits

Thank you to bunnycore, Qwen Team, ertghiu256, TeichAI for the wonderful fine tunes and base models that made this merge possible! Built by ZeroXClem Team β€” merging distillations, hugging intellect and ideas into tangible weights. MergeKit mastery allows full distilled insight in one mighty little package.

Mini in name. Infinite in mind. πŸ›Έ

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