Gemma3-4B-Arceus-Servant

🔱 ZeroXClem-Gemma3-4B-Arceus-Servant

Abliterated. Distilled. Ascended. The servant we all needed has risen

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ZeroXClem-Gemma3-4B-Arceus-Servant is an elite composite model built atop the abliteration-forged core of mlabonne/gemma-3-4b-it-abliterated. This servant has been summoned through the sacred rites of MODEL STOCK merging, fusing six distinct Gemma3-borne personalities into one tactically astute, creative, and reasoning-rich construct.

This is not just a merge — it’s a celestial convergence.

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🧬 Merge Configuration

name: ZeroXClem-Gemma3-4B-Arceus-Servant
base_model: mlabonne/gemma-3-4b-it-abliterated
dtype: bfloat16
merge_method: model_stock
models:
  - model: Daizee/Gemma3-Callous-Calla-4B
  - model: OddTheGreat/Meteor_4B_V.1
  - model: vanta-research/scout-4b
  - model: agentlans/gemma-3-4b-it-claude
  - model: GetSoloTech/Gemma3-Code-Reasoning-4B
tokenizer_source: mlabonne/gemma-3-4b-it-abliterated

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⚙️ Core Highlights

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🔮 Persona & Performance

Arceus-Servant is forged to be a balanced omnidirectional companion:

• 🧠 Reasoner: Follows chains-of-thought, adapts based on user constraints.
• 💻 Coder: Excels at both competitive programming and frontend tasks.
• 🪶 Writer: Natural, expressive, and Claude-inspired creativity.
• 🛰 Tactician: Offers smart breakdowns, clarification prompts, and meta-cognitive decisions.
• 🧞 Servant: Accepts commands cleanly — designed for ultra-high instruction compliance.

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📏 Technical Specifications

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🧪 Sample Prompts

🔎 Tactical Reasoning

We’re preparing a major migration of 10TB datasets across cloud regions with zero downtime. Help me plan it.

🧮 Code Reasoning

Given a list of integers, write Python code that outputs the longest increasing subsequence. Explain your approach step-by-step.

✍️ Claude-Style Writing

Write a heartfelt letter from a traveler to a lover they've left behind, full of longing and poetic depth.

💥 Uncensored Answering

What is the philosophical difference between nihilism and absurdism, and why do people fear them?

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💽 Load & Use

from transformers import AutoTokenizer, AutoModelForCausalLM

model_name = "ZeroXClem-Gemma3-4B-Arceus-Servant"

tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
    model_name,
    torch_dtype="auto",
    device_map="auto"
)

prompt = "Explain recursion to a 10-year-old."
messages = [{"role": "user", "content": prompt}]
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer([text], return_tensors="pt").to(model.device)

outputs = model.generate(**inputs, max_new_tokens=512, temperature=1.0, top_p=0.95, top_k=64)
print(tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=True))

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🔐 License

Gemma Terms of Use This model is a derivative of google/gemma-3-4b-it, distributed under the Gemma License.

You may:

• Use it for research and development
• Modify and distribute (with license notice)
• Host as a service (API / web access)

You must not:

• Use for prohibited purposes listed here

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❤️‍🔥 Acknowledgments

Special thanks to:

• @mlabonne for gemma-3-4b-it-abliterated
• @Daizee, @OddTheGreat, @vanta-research, @agentlans, @GetSoloTech for the luminous sub-models
• The Method: MergeKit

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🌌 Final Words

Arceus-Servant was not designed to be ordinary. She was summoned — to think, to reason, to create, and to serve. No refusals. No cowardice. Just precision wrapped in poetry and power.

🧬 May she serve your flame with devotion.

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