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Model: Ademola265/Qwen3-4B-Thinking-2507-GLM-4.7-Distilled-GGUF Source: Original Platform
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---
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language:
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- en
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- zh
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license: apache-2.0
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base_model: Jackrong/DASD-4B-Thinking-2507-GRPO-v2
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tags:
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- qwen3
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- unsloth
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- text-generation
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- reasoning
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- math
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- grpo
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- sft
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- distillation
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- conversational
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- glm-4.7
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pipeline_tag: text-generation
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---
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# Qwen3-4B-Thinking-2507-GLM-4.7-Distilled
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**Qwen3-4B-Thinking-2507-GLM-4.7-Distilled** is a fine-tuned model built upon the GRPO-optimized `Jackrong/DASD-4B-Thinking-2507-GRPO-v2` (originally based on [`Qwen/Qwen3-4B-Thinking-2507`](https://huggingface.co/Qwen/Qwen3-4B-Thinking-2507)). This model was developed using a Supervised Fine-Tuning (SFT) strategy heavily distilled from the GLM-4.7 model series (at a default temperature of 1.0), with a central focus on multi-turn conversational alignment and **structured Chain-of-Thought (CoT) execution**.
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🎯 **Core Improvement:**
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The primary objective of this fine-tuning was to transform the model's reasoning pattern for everyday and lightweight tasks. Instead of the typical linear, free-associative, and highly self-correcting ("think-as-you-go") stream of consciousness, this model has learned to adopt a highly confident, **"Plan-then-Execute"** paradigm. It systematically breaks down tasks into logical outlines and executes modular, report-like responses without unnecessary self-doubt or hesitation.
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---
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## 🧬 Training Pipeline Overview
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This model is the culmination of two sequential training stages targeting mathematical reasoning and conversational CoT tracking:
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```text
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Qwen/Qwen3-4B-Thinking-2507
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│
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▼ Stage 0: GRPO (RL on Math & Reasoning)
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DASD-4B-Thinking-2507-GRPO-v2
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│
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▼ Stage 1: SFT with GLM-4.7 Series Distilled Datasets (T=1.0)
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Qwen3-4B-Thinking-2507-GLM-4.7-Distilled ← (this model)
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```
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### 🧠 Chain of Thought (CoT) Evolution: Base vs. Distilled
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A significant shift in the model's reasoning style is observed after distillation from the GLM-4.7 series data. The model transitions from a **spontaneous thinker** into a **structured planner**:
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| 🎯 Feature | 🌀 Base Model (Qwen3-4B-Thinking) | ✨ Distilled Model (GLM-4.7-Distilled) |
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| :--- | :--- | :--- |
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| **Thinking Style** | 🌊 Linear, stream-of-consciousness | 🧱 Modularized, report-like |
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| **Execution** | 🏃 Thinks on the fly, writes as it thinks | 📝 "Plan-then-Execute" framework |
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| **Structure** | 🔀 Unstructured, organic self-correction mid-thought | 📑 Highly structured with headings & logical phases |
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| **Confidence** | 🤔 High self-doubt ("Wait...", "Maybe...", "Should I...") | 🚀 Highly confident, rarely hesitates |
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| **Output Tone** | 🗣️ Conversational, exploring multiple paths | 📊 Objective, direct, and systematic |
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**🌟 Key Takeaway:**
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Through the GLM-4.7 dataset distillation, the model successfully learned the **modular thinking paradigm**. Instead of continuously questioning itself, it now *breaks down tasks, creates a clear outline, and systematically executes each step* like writing a formal report.
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---
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## 📚 Stage Details
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### Stage 0 — GRPO Reinforcement Learning: `DASD-4B-Thinking-2507-GRPO-v2`
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Starting from the base model `Qwen/Qwen3-4B-Thinking-2507`, Group Relative Policy Optimization (GRPO) was applied. This stage consisted of:
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- **Cold Start:** Fine-tuning on the [`unsloth/OpenMathReasoning-mini`](https://huggingface.co/datasets/unsloth/OpenMathReasoning-mini) dataset.
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- **Reinforcement Learning:** Applying GRPO via the [`open-r1/DAPO-Math-17k-Processed`](https://huggingface.co/datasets/open-r1/DAPO-Math-17k-Processed) dataset.
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This stage significantly improved the model's:
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- Correctness on math problem solving
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- Step-by-step logical reasoning
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- Reward signal alignment for verifiable tasks
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---
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### Stage 1 — SFT GLM-4.7 Distillation (T=1.0): `Qwen3-4B-Thinking-2507-GLM-4.7-Distilled` (this model)
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Building on the reasoning foundation of `DASD-4B-Thinking-2507-GRPO-v2`, Stage 1 SFT was performed using a mixed dataset heavily utilizing **GLM-4.7** synthetic data generated at a **default temperature of 1.0**, along with multi-turn alignments.
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Higher-temperature data introduces greater **lexical diversity, broader mode coverage, and more formatted/structured chain-of-thought traces**, enabling the model to generalize better across diverse conversational reasoning patterns and problem domains. It helps the model handle multi-turn conversations effectively while protecting its internal structure of `<think>...</think>` tracking.
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---
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## 🗂️ All Datasets Used
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| Stage | Dataset | Purpose |
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|-------|---------|---------|
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| GRPO (Cold Start) | [`unsloth/OpenMathReasoning-mini`](https://huggingface.co/datasets/unsloth/OpenMathReasoning-mini) | Initial foundational mathematical reasoning |
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| GRPO (RL) | [`open-r1/DAPO-Math-17k-Processed`](https://huggingface.co/datasets/open-r1/DAPO-Math-17k-Processed) | Math & reasoning RL training via GRPO |
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| SFT Distillation | [`Alibaba-Apsara/Superior-Reasoning-SFT-gpt-oss-120b`](https://huggingface.co/datasets/Alibaba-Apsara/Superior-Reasoning-SFT-gpt-oss-120b) (Stage 2) | Diverse reasoning structures |
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| SFT Distillation | [`Jackrong/glm-4.7-multiturn-CoT`](https://huggingface.co/datasets/Jackrong/glm-4.7-multiturn-CoT) | Multi-turn CoT alignment |
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| SFT Distillation | [`Jackrong/glm-4.7-Superior-Reasoning-stage1`](https://huggingface.co/datasets/Jackrong/glm-4.7-Superior-Reasoning-stage1) | Enhanced fundamental reasoning |
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| SFT Distillation | [`TeichAI/glm-4.7-2000x`](https://huggingface.co/datasets/TeichAI/glm-4.7-2000x) | Generalization and lexical diversity |
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| SFT Distillation | [`Jackrong/MultiReason-ChatAlpaca`](https://huggingface.co/datasets/Jackrong/MultiReason-ChatAlpaca) | Conversational multi-turn tracking |
|
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---
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## 🏃 Quickstart
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_name = "Jackrong/Qwen3-4B-Thinking-2507-GLM-4.7-Distilled"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype="auto", device_map="auto")
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messages = [
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{"role": "user", "content": "Solve: find all real solutions to x^3 - 6x^2 + 11x - 6 = 0."}
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]
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text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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inputs = tokenizer([text], return_tensors="pt").to(model.device)
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outputs = model.generate(**inputs, max_new_tokens=4096)
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response = tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=True)
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print(response)
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```
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> **Tip:** This model naturally generates `<think>...</think>` reasoning traces before the final answer. You can parse these to inspect the chain-of-thought.
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---
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## 📋 Model Details
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| Attribute | Value |
|
||||
|-----------|-------|
|
||||
| **Base Model** | `Jackrong/DASD-4B-Thinking-2507-GRPO-v2` |
|
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| **Architecture** | Qwen3 (4B Dense) |
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| **License** | Apache 2.0 |
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| **Language(s)** | English, Chinese |
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| **Training Framework** | [Unsloth](https://github.com/unslothai/unsloth) + Hugging Face TRL |
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| **RL Algorithm** | GRPO (Group Relative Policy Optimization) |
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| **Fine-tuning Method** | SFT (GLM-4.7 Distillation at T=1.0) |
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| **Developed by** | Jackrong |
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---
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## ⚠️ Limitations & Intended Use
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- This model is intended for **research and educational purposes** related to reasoning and mathematical problem-solving.
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- While mathematical and logical reasoning capabilities have been enhanced, the model may still produce incorrect answers or hallucinations — always verify outputs on critical tasks.
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- The model inherits the capabilities and limitations of the underlying `Qwen3-4B-Thinking-2507` architecture.
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- Not intended for deployment in high-stakes applications without additional safety evaluation.
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---
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## 📎 Related Models
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||||
|
||||
| Model | Description |
|
||||
|-------|-------------|
|
||||
| [`Qwen/Qwen3-4B-Thinking-2507`](https://huggingface.co/Qwen/Qwen3-4B-Thinking-2507) | Base model |
|
||||
| [`Jackrong/DASD-4B-Thinking-2507-GRPO-v2`](https://huggingface.co/Jackrong/DASD-4B-Thinking-2507-GRPO-v2) | After GRPO RL training |
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| [`Jackrong/Qwen3-4B-Thinking-2507-GLM-4.7-Distilled`](https://huggingface.co/Jackrong/Qwen3-4B-Thinking-2507-GLM-4.7-Distilled) | **This model** — GLM-4.7 Distilled |
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---
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## 🙏 Acknowledgements
|
||||
|
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- [Zhipu AI](https://huggingface.co/THUDM) for the GLM-4.7 model series capability
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- [Alibaba Cloud Apsara Lab](https://huggingface.co/Alibaba-Apsara) for reasoning datasets
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- [Open-R1](https://huggingface.co/open-r1) for the DAPO Math dataset
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- [Unsloth](https://github.com/unslothai/unsloth) for efficient fine-tuning infrastructure
|
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- [Qwen Team](https://huggingface.co/Qwen) for the excellent base model
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{
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"architectures": [
|
||||
"Qwen3ForCausalLM"
|
||||
],
|
||||
"attention_bias": false,
|
||||
"attention_dropout": 0.0,
|
||||
"torch_dtype": "bfloat16",
|
||||
"eos_token_id": 151645,
|
||||
"head_dim": 128,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 2560,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 9728,
|
||||
"layer_types": [
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention"
|
||||
],
|
||||
"max_position_embeddings": 262144,
|
||||
"max_window_layers": 36,
|
||||
"model_type": "qwen3",
|
||||
"num_attention_heads": 32,
|
||||
"num_hidden_layers": 36,
|
||||
"num_key_value_heads": 8,
|
||||
"pad_token_id": 151654,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_scaling": null,
|
||||
"rope_theta": 5000000,
|
||||
"sliding_window": null,
|
||||
"tie_word_embeddings": true,
|
||||
"unsloth_fixed": true,
|
||||
"unsloth_version": "2026.2.1",
|
||||
"use_cache": true,
|
||||
"use_sliding_window": false,
|
||||
"vocab_size": 151936
|
||||
}
|
||||
Reference in New Issue
Block a user