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Qwen3-Space.Agent.Claude.Un…/README.md
ModelHub XC 3ac88b8c2d 初始化项目,由ModelHub XC社区提供模型
Model: WithinUsAI/Qwen3-Space.Agent.Claude.Uncensored-4B
Source: Original Platform
2026-06-05 21:08:10 +08:00

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---
base_model:
- Qwen/Qwen3-4B-Thinking-2507
- nightmedia/Qwen3-4B-Agent-Claude-Gemini
- SpaceTimee/Suri-Qwen-3.1-4B-Uncensored-Preview
library_name: transformers
tags:
- mergekit
- merge
datasets:
- unalignment/toxic-dpo-v0.2
- NobodyExistsOnTheInternet/ToxicQAFinal
- Orion-zhen/dpo-toxic-zh
---
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.
🧬 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.
🧠 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
⚙️ 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
📦 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
🚀 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
🧪 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
📊 Expected Performance Profile
Capability Strength
Reasoning High
Agent behavior High
Coding High
Context handling High
Safety filtering Low (intentionally reduced)
📚 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)
📜 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
🙏 Acknowledgements
* Alibaba Qwen team
* Open-source agent model contributors
* GGUF / llama.cpp ecosystem
* AI alignment & safety research community
🔗 Links
* Model: https://huggingface.co/WithinUsAI/Qwen3-Space.Agent.Claude-Uncensored-4B
* Organization: https://huggingface.co/WithinUsAI
🧩 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.