Qwen3-Space.Agent.Claude.Uncensored-4B

Qwen3-Space.Agent.Claude-Uncensored-4B

📌 Model Overview

Model Name: WithinUsAI/Qwen3-Space.Agent.Claude-Uncensored-4B Organization: Within Us AI Model Type: Agentic Reasoning LLM (Uncensored Variant) Parameter Size: 4B Architecture: Qwen 3 (Dense Transformer) Context Length: ~32K tokens Primary Focus: Agent workflows + uncensored reasoning + long-context tasks

This model is a multi-source merged Qwen3-based agent, designed to combine:

• 🧠 Reasoning (“thinking” models)
• 🤖 Agent/tool-use behavior
• 🔓 Reduced refusal / uncensored outputs

It aims to deliver a compact, flexible, and less-restricted AI system for experimentation, research, and local deployment. 

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🧬 Architecture & Lineage

Base Composition

This model is a merge of multiple Qwen3-derived systems, including:

• Qwen3-4B Thinking (reasoning-focused)
• Qwen3 Agent Claude/Gemini-style model
• Uncensored Qwen3 variants

These were combined into a single unified 4B model to blend capabilities. 

What That Creates

A hybrid model with:

• Reasoning depth (thinking models)
• Structured outputs (agent models)
• Reduced refusal behavior (uncensored variants)

Think of it like a three-engine spacecraft 🚀 Each engine specialized… now flying as one system.

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🧠 Core Design Philosophy

Fuse the best behaviors… remove the limits… keep it small enough to run anywhere.

Key Goals:

• Merge reasoning + agent + uncensored traits
• Enable long-context problem solving
• Preserve performance in a 4B footprint
• Support real-world agent pipelines

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⚙️ Key Capabilities

🧠 Reasoning

• Step-by-step thinking
• Multi-hop problem solving
• Long-context coherence (~32K tokens)

🤖 Agentic Behavior

• Task decomposition
• Tool-use compatibility
• Structured outputs (JSON, actions)

💻 Coding

• Code generation & debugging
• Algorithm reasoning
• SWE-style workflows

🔓 Uncensored Behavior

• Reduced refusal rates
• More permissive responses
• Suitable for:
  • Alignment research
  • Safety testing
  • Edge-case exploration

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📦 Deployment

Supported Environments

• llama.cpp
• LM Studio
• Ollama (GGUF / compatible builds depending on conversion)

Runtime Characteristics

• ~4B parameters → runs on consumer GPUs / strong CPUs
• ~32K context → supports long conversations and documents 

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🚀 Intended Use

✅ Ideal Use Cases

• Agent frameworks (tool-calling systems)
• Long-context reasoning tasks
• AI experimentation (uncensored behavior)
• Local assistants with fewer restrictions
• Alignment and safety research

⚠️ Important Considerations

• Outputs are less restricted than aligned models
• May generate sensitive or unsafe content
• Requires external moderation or guardrails for production use

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🧪 Training & Merge Methodology

This model follows a merge-based synthesis pipeline:

1. Select complementary base models:
   • Reasoning-focused
   • Agent-focused
   • Uncensored variants
2. Merge weights into unified architecture
3. Align behavior using preference tuning (DPO-style datasets)
4. Optimize for:
   • Reduced refusals
   • Stable outputs
   • Agent usability 

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📊 Expected Performance Profile

Capability Strength Reasoning High Agent behavior High Coding High Context handling High Safety filtering Low (intentionally reduced)

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📚 Datasets & Training Sources

Following Within Us AI methodology:

• Proprietary datasets created by Within Us AI
• Third-party datasets used without ownership claims
• Includes:
  • Reasoning traces
  • Agent workflows
  • Preference optimization (DPO-style tuning)

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📜 License

License Type: Inherits from Qwen / base model ecosystem

Attribution Notes:

• Base models: Qwen (Alibaba ecosystem)
• Merge & methodology: Within Us AI
• Additional model influences (Claude-style / Gemini-style behaviors via distillation/merging)
• Third-party datasets used without ownership claims
• Credit belongs to original creators

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🙏 Acknowledgements

• Alibaba Qwen team
• Open-source agent model contributors
• GGUF / llama.cpp ecosystem
• AI alignment & safety research community

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🔗 Links

• Model: https://huggingface.co/WithinUsAI/Qwen3-Space.Agent.Claude-Uncensored-4B
• Organization: https://huggingface.co/WithinUsAI

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🧩 Closing Note

This model feels like a hybrid intelligence node 🌌

Part thinker. Part agent. Part rule-breaker.

All compressed into 4B parameters that punch way above their weight.