commit a20db7dcabccc77d819e6ac2f47da7d5df67ea62 Author: ModelHub XC Date: Fri Aug 28 20:12:19 2026 +0800 初始化项目，由ModelHub XC社区提供模型 Model: manvadariya1/Zynthos-Reasoning-4B-GGUF Source: Original Platform diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..289c5f0 --- /dev/null +++ b/.gitattributes @@ -0,0 +1,38 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text +Zynthos-Reasoning-4B-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text +Zynthos-Reasoning-4B-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text +Zynthos-Reasoning-4B-F16.gguf filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000..65695ae --- /dev/null +++ b/README.md @@ -0,0 +1,99 @@ +--- +license: apache-2.0 +base_model: Qwen/Qwen3-4B-Base +model_creator: Qwen +model_name: Zynthos Reasoning 4B +pipeline_tag: text-generation +quantized_by: manvadariya1 +language: +- en +tags: +- text-generation +- gguf +- reasoning +- grpo +- reinforcement-learning +- math +- code +- agentic-ai +- rag +- mcp +--- + +# 🌀 Zynthos-Reasoning-4B (The Edge Reasoning Revolution) + +Zynthos-Reasoning-4B is a highly specialized, compute-optimized local reasoning model engineered to execute complex multi-step logical chain-of-thought operations directly at the edge. + +By taking the raw architectural foundation of **Qwen3-4B-Base** and applying an intensive, dual-stage training blueprint (Supervised Fine-Tuning + Group Relative Policy Optimization), Zynthos introduces an incredibly agile, low-overhead intelligence layer that matches the thinking depth of models many times its size. + +--- + +## 🚀 True Local Sovereignty: The Multi-Agent & RAG Edge Engine + +Large reasoning engines are too slow and expensive to act as real-time workers. **Zynthos-Reasoning-4B** bridges this gap perfectly, acting as an efficient local processor designed for modern AI architectures: + +* **⚡ Agentic AI Ecosystems:** Natively executes autonomous agent loops. It easily maps out complex, multi-layered action plans before calling local programmatic tools or executing tool pathways. +* **📂 Advanced Local RAG Sorting:** Rather than blindly extracting vector chunks, Zynthos reads retrieved context pipelines with adaptive reasoning—filtering out noise, evaluating facts, and synthesizing accurate answers without hallucinating. +* **🔌 Native MCP Architecture Integration:** Ideal for driving **Model Context Protocol (MCP)** setups. It acts as the local brain that translates raw server signals, constructs valid infrastructure connections, and safely manages automated software workflows. +* **🔢 Adaptive Mathematical Reasoning:** Features an activated `` loop that dynamically scales its cognitive effort based on problem complexity—effortlessly tackling advanced algebra, code logic bugs, and structural derivations. + +--- + +## 🛠️ The Paradigm-Shifting Training Pipeline + +Zynthos proves that ultra-curated data mixtures can break through the brute-force compute bottleneck. The model was aligned using a specialized asset pipeline: + +1. **Stage I: High-Fidelity SFT Alignment:** Instilled command-following structures and rigorous multi-turn code dialogue styles using `deepmath_15k_hard_sft.jsonl`, `codefeedback_sft_15k.jsonl`, and high-density `claude_traces_sft.jsonl` data sets. +2. **Stage II: Accelerated GRPO Reinforcement Learning:** Rather than running an unguided 100,000-iteration cluster run, Zynthos underwent a highly targeted **450-iteration GRPO reinforcement learning trajectory** across specialized mathematical and programming corpora (`deepmath_grpo_60k`, `code_reasoning_grpo_43k`, `stratos_grpo_17k`, `taco_only_grpo_35k`, and `codefeedback_grpo_18k`). + +> **💡 The Efficiency Breakthrough:** This accelerated 450-iteration training setup demonstrates that precision data curation enables a 4B parameter model to achieve deep logical self-correction capabilities at a fraction of standard industry compute costs. + +--- + +## 📊 Quantization & Hardware Deployment Matrix + +Every GGUF block in this lineup has been meticulously compiled to safeguard tensor values, providing predictable memory tracking and sub-millisecond execution loops across your graphics layers. + +> ### ⭐ Target Deployment Recommendation +> * **For Absolute Peak Precision:** **`Zynthos-Reasoning-4B-F16.gguf` is the highly recommended choice.** It retains 100% of the raw, unquantized model weights, providing the ultimate logical depth, perfect tool-calling syntax, and total resistance to token regression. +> * **For Resource-Constrained Hardware:** Use **`Zynthos-Reasoning-4B-Q4_K_M.gguf`**. At just 2.4 GB, it runs flawlessly at maximum execution speeds on low-end consumer hardware or budget machines with as little as **4 GB of total system RAM**. + +| File Name | Precision Weights | File Size | Recommended System RAM | Core Deployment Target | +| :--- | :--- | :--- | :--- | :--- | +| **`Zynthos-Reasoning-4B-F16.gguf`** | **Full FP16 Master** | **~7.5 GB** | **12 GB RAM** | 🏆 **Recommended Tier:** Sovereign server automation, deep math, & production agent pipelines | +| `Zynthos-Reasoning-4B-Q8_0.gguf` | 8-bit Standard | ~4.0 GB | 8 GB RAM | Balanced Tier: Scalable local RAG scanning and heavy contextual extraction | +| `Zynthos-Reasoning-4B-Q4_K_M.gguf` | 4-bit Medium | ~2.4 GB | **4 GB RAM** | Ultra-Fast Tier: Agile on-device agents, low-end laptop setups, and ultra-budget edge containers | + +--- + +## 💻 Quickstart Implementation Playbook + +### 1. Drag-and-Drop Local Runtime (LM Studio) +1. Download the recommended `Zynthos-Reasoning-4B-F16.gguf` variant directly from the files menu. +2. Drop the asset file into your dedicated local model paths directory. +3. Select the model from your dashboard dropdown, maximize **GPU Offload** settings, and start chatting locally with full chain-of-thought support. + +### 2. Programmatic Agentic Orchestration (`llama-cpp-python`) +Build local background agent tools, automated MCP systems, or RAG processors using this direct Python automation layout: + +```python +from llama_cpp import Llama + +# Initialize the recommended pristine FP16 engine lane +llm = Llama( + model_path="./Zynthos-Reasoning-4B-F16.gguf", + n_ctx=8192, # Expanded context window for deep chain-of-thought trace paths + n_gpu_layers=-1 # Fully offload model weight processing layers to your local GPU +) + +prompt = """<|im_start|>system +You are Zynthos-Reasoning, a model that thinks carefully before responding. Show your step-by-step thinking inside a block, and output your final answer outside. +<|im_end|> +<|im_start|>user +Write an optimized Python function to securely manage incoming Model Context Protocol (MCP) data payloads, then verify its time complexity.<|im_end|> +<|im_start|>assistant +""" + +output = llm(prompt, max_tokens=1024, stop=["<|im_end|>"]) +print(output['choices'][0]['text']) + diff --git a/Zynthos-Reasoning-4B-F16.gguf b/Zynthos-Reasoning-4B-F16.gguf new file mode 100644 index 0000000..0831eb6 --- /dev/null +++ b/Zynthos-Reasoning-4B-F16.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:31ae8f46be09490fe5714ce87b7ab3ab44e563ee37eae324d075d0eb19977abc +size 8051284864 diff --git a/Zynthos-Reasoning-4B-Q4_K_M.gguf b/Zynthos-Reasoning-4B-Q4_K_M.gguf new file mode 100644 index 0000000..67d341b --- /dev/null +++ b/Zynthos-Reasoning-4B-Q4_K_M.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:1572523f0cd03d0df47f97a27c6f82d7e6f3feed52ab280cc1c4dece7444d0fc +size 2497280384 diff --git a/Zynthos-Reasoning-4B-Q8_0.gguf b/Zynthos-Reasoning-4B-Q8_0.gguf new file mode 100644 index 0000000..49a6034 --- /dev/null +++ b/Zynthos-Reasoning-4B-Q8_0.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6b84c508528a904cdd104f2f6a021fa6872313c135907e03151f0efa5a4e96eb +size 4280404864