yuxinlu1/qwen3-6-27b-chinese-realistic-fiction-lora-v1

📚 Qwen3.6-27B Chinese Realistic Fiction LoRA — v1

A LoRA adapter that pushes Qwen3.6-27B toward a Chinese realistic fiction prose voice for local long-form novel drafting.

The style direction is intentionally narrow:

• restrained, cold, plain narration
• dark humor
• working-class / everyday-life subject matter
• emotional understatement, silence, and negative space

The goal is for outputs to read more like a quiet realist short story in Chinese, and less like a web novel or a "polished AI essay."

Typical use cases:

• drafting scenes inside a longer novel project
• experimenting with literary style on a local model
• offline / privacy-respecting creative writing

This is an adapter only. It does not include base model weights, training data, or any copyrighted source material.

---

🧭 About the v1 / v2 Series

This repo is part of a small series of Chinese fiction LoRAs. The series is split into two generations.

v1 — Style retraining

• Trained with SFT to move the base model away from generic AI prose and toward a specific Chinese literary style.
• Within the v1 series there will be multiple LoRAs in different style directions. This repo is the realistic fiction direction.
• Format: GGUF LoRA (for llama.cpp / local inference).

v2 — Style + behavioral fine-tuning

• Adds DPO, larger amounts of synthetic data, and on-policy sampling on top of the v1 recipe.
• Output is more precise, more stable, and shows fewer habitual "AI-shaped" patterns.
• Released in multiple formats: HF PEFT safetensors / GGUF LoRA / MLX LoRA.

This repo is a v1 (style) adapter. v2 models are documented in their own model cards.

---

🌱 Status

Field	Value
Version	v1 (style)
Style	Chinese realistic fiction
Format	GGUF LoRA
Base model	Qwen3.6-27B
Language	Chinese
Use case	fiction drafting

---

🚀 Example llama.cpp Usage

llama-server.exe ^
  -m path\to\your\base-model.gguf ^
  --lora path\to\qwen3_6_27b_novel_lora.gguf ^
  --port 18084 ^
  --ctx-size 16384 ^
  --n-gpu-layers 99 ^
  --cache-type-k q4_0 ^
  --cache-type-v q4_0 ^
  --flash-attn

Then point an OpenAI-compatible client (or the Novel pipeline) at the local server:

$env:LLM_BASE_URL="http://localhost:18084/v1"
$env:LLM_API_KEY="local"
$env:LLM_MODEL="your-model-name.gguf"

---

🧪 Intended Use

This LoRA is intended for:

• local long-form Chinese fiction drafting
• experimenting with restrained, literary prose styles
• creative writing assistance in a human-in-the-loop pipeline
• offline / privacy-respecting writing workflows

It is not intended for:

• impersonating any specific living author
• generating defamatory or harmful content about real people
• mass-producing low-quality content for spam or content farms
• any use that violates the base model's license or local laws

---

⚠️ Limitations

• This is a v1 style adapter. It changes prose voice; it does not guarantee plot coherence or long-context consistency.
• Long-form continuity (characters, foreshadowing, timeline) needs to come from a writing pipeline or from the author, not from the LoRA.
• Output quality depends heavily on the base model, quantization, prompt, and outline quality.
• Style strength varies across sampling settings and hardware.
• The LoRA is narrow on purpose: if you ask it to write romance, fantasy, or web-novel-style action, results will be off-style.

---

🛡️ Safety and Legal Notes

• No copyrighted novels, private manuscripts, or proprietary datasets are distributed in this repository.
• This LoRA is not designed to imitate any specific living author.
• Generated text is fiction. Any resemblance to real people or events is coincidental.
• Users are responsible for following applicable laws and the base model's license when generating, storing, or publishing output.

---

📜 License

• LoRA adapter: MIT
• Base model: governed by its own license (see Qwen3.6-27B upstream terms).

You are responsible for complying with the base model's license when combining this LoRA with the base weights.

---

🔗 Related Project

This LoRA was built with a local-first novel writing pipeline in mind:

• Novel pipeline: https://github.com/DuckTraDo/Novel

The pipeline handles outlines, scene-level context, story memory, and continuity checks; this LoRA handles prose style. They are designed to be used together.