Jackrong/gpt-oss-120b-Distill-Qwen3-4B-Thinking-GGUF

📦 Model Card: Jackrong/gpt-oss-120b-Distill-Qwen3-4B-Thinking

Key Property	Value
Model ID	Jackrong/gpt-oss-120b-Distill-Qwen3-4B-Thinking
License	apache-2.0
Author(s)	Jackrong, gpt‑oss team, Qwen authors
Base Model	gpt-oss-120b-high (complex reasoning dataset distilled)
Target Size	~ 4B parameters (Qwen3‑4B distilled version)

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🔍 Overview

A deeply distilled and fine-tuned variant of the large‑language model gpt-oss-120b-high, optimized for human‑friendly, high‑fidelity reasoning. The model preserves the original’s multi‑step thinking patterns while compressing them onto a lightweight 4B‑parameter backbone (the “Distill‑Qwen3” architecture). Its signature feature is an explicit point‑by‑point thought chain that makes intricate logic transparent and easy to follow, ideal for education, technical support, and analytical tasks.

💡 Think of it as the “thinking mode” you’d expect from a massive

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🛠️ Technical Details

Aspect	Specification
Source Model	gpt-oss‑120b‑high (complex reasoning dataset distilled)
Distillation Target	Qwen3‑4B architecture
Supervised Fine‑Tuning (SFT)	~ 30,000 examples drawn from the source’s high‑fidelity reasoning corpus
Training Hardware	Single NVIDIA H100‑80GB GPU
Max Context Length	32 768 tokens – enables multi‑paragraph, long‑form reasoning without truncation
Reasoning Style	Default: Bullet‑point “thought chain” output (e.g., • Step 1 → …\n• Step 2 → …)

🎯 Recommended Use Cases

Case	When to use
Technical tutorials	Leverage bullet‑point logic for stepwise code walkthroughs
Complex queries (e.g., math, engineering)	The model’s deep reasoning helps avoid oversimplified answers
User education	Clear, scannable outputs aid learning and reduce confusion
Moderation/analysis	The structured format makes it easier to parse responses programmatically

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📚 Credits & Contributors

• gpt‑oss team: Provided the high‑fidelity complex‑reasoning dataset.
• Qwen3 authors: Open‑source architecture used as distillation target.
• Jackrong: Implemented the final SFT and packaging for Hugging Face Hub.

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