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chore(model gallery): 🤖 add new models via gallery agent
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gallery/index.yaml

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- filename: Qwen3-Grand-Horror-Light-1.7B.Q4_K_M.gguf
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sha256: cbbb0c5f6874130a8ae253377fdc7ad25fa2c1e9bb45f1aaad88db853ef985dc
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uri: huggingface://mradermacher/Qwen3-Grand-Horror-Light-1.7B-GGUF/Qwen3-Grand-Horror-Light-1.7B.Q4_K_M.gguf
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- !!merge <<: *qwen3
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name: "deepwerewolf-qwen3-8b-grpo-agentic-chinese"
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urls:
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- https://huggingface.co/mradermacher/DeepWereWolf-Qwen3-8B-Grpo-Agentic-Chinese-GGUF
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description: |
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**Model Name:** DeepWereWolf-Qwen3-8B-Grpo-Agentic-Chinese
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**Base Model:** Qwen/Qwen3-8B
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**Author:** haowu11 (original training), mradermacher (GGUF quantization)
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**Language:** Chinese (with strong English support)
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**Model Type:** Instruction-tuned, agentic large language model
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**Architecture:** Qwen3-8B (8-billion parameter autoregressive transformer)
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**Fine-Tuning:** Trained using Grouped-Response Policy Optimization (GrPO) for enhanced reasoning and agent-like behavior
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**Use Case:** Ideal for complex reasoning, multi-step tasks, code generation, and interactive agent applications in Chinese and English
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**Quantized By:** mradermacher (GGUF format, available in multiple quantization levels from Q2_K to Q8_0 and f16)
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**Overview:**
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DeepWereWolf-Qwen3-8B-Grpo-Agentic-Chinese is a high-performance, instruction-tuned variant of Qwen3-8B, specifically optimized for agentic workflows with strong reasoning and task execution capabilities. Built upon the Qwen3-8B foundation, it is fine-tuned using Grouped-Response Policy Optimization (GrPO) to improve decision-making and long-horizon task performance. The model excels in multi-step reasoning, dialogue, and autonomous task execution, making it particularly well-suited for AI agent applications.
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This version is available in multiple GGUF quantizations (from Q2_K to Q8_0), enabling efficient deployment on consumer hardware. The original full-precision model is available at `haowu11/DeepWereWolf-Qwen3-8B-Grpo-Agentic-Chinese`, while the quantized versions are hosted by mradermacher for easy local inference.
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**Key Features:**
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- Trained for agentic behavior with advanced reasoning
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- Strong performance in Chinese and bilingual tasks
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- Optimized for local deployment via GGUF quantization
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- Supports multi-turn dialogue and complex instruction following
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**Use with:** llama.cpp, Ollama, Text Generation WebUI, and other GGUF-compatible tools.
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**Note:** The GGUF files are quantized versions by mradermacher; the original model was created by haowu11 based on Qwen3-8B and the DeepWerewolf project.
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overrides:
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parameters:
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model: DeepWereWolf-Qwen3-8B-Grpo-Agentic-Chinese.Q4_K_M.gguf
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files:
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- filename: DeepWereWolf-Qwen3-8B-Grpo-Agentic-Chinese.Q4_K_M.gguf
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sha256: 32a341badc695d9e8bc1bdae92c67b81295d6e3cfd8e901a508f323718db5141
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uri: huggingface://mradermacher/DeepWereWolf-Qwen3-8B-Grpo-Agentic-Chinese-GGUF/DeepWereWolf-Qwen3-8B-Grpo-Agentic-Chinese.Q4_K_M.gguf

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