Instructions to use zuiho-kai/jianghan-runtime-v5-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use zuiho-kai/jianghan-runtime-v5-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.5-4B") model = PeftModel.from_pretrained(base_model, "zuiho-kai/jianghan-runtime-v5-lora") - Notebooks
- Google Colab
- Kaggle
Jianghan Runtime v5 LoRA
LoRA adapter for the Jianghan runtime roleplay candidate.
GitHub runtime repository:
https://github.com/zuiho-kai/jianghan-roleplay-data-pipeline
Training artifacts dataset:
https://huggingface.co/datasets/zuiho-kai/jianghan-roleplay-training-artifacts
Usage
git clone https://github.com/zuiho-kai/jianghan-roleplay-data-pipeline.git
cd jianghan-roleplay-data-pipeline
python scripts/jianghan_runtime_chat.py \
--model Qwen/Qwen3.5-4B \
--adapter zuiho-kai/jianghan-runtime-v5-lora \
--profile role \
--stage 第三阶段 \
--prompt 猫灯们把简单账目做成了艺术展,你要处理这件事。 \
--hide-stage-prefix \
--retry 2
Current promoted stack:
Qwen/Qwen3.5-4B + v5 checkpoint-150 + runtime_rag_v1 + phase-hidden + audit/retry
Quick online deploy
For model + runtime RAG HTTP serving, use the GitHub quick deploy guide:
https://github.com/zuiho-kai/jianghan-roleplay-data-pipeline/blob/main/docs/QUICK_DEPLOY.md
The service exposes GET /health, POST /rag, and POST /chat.
Runtime RAG files
The adapter does not contain the RAG index. Runtime RAG code and the minimal deployable index live in the GitHub repo:
- GitHub runtime repo: https://github.com/zuiho-kai/jianghan-roleplay-data-pipeline
scripts/jianghan_runtime_rag.pydata/world/worldbook/worldbook_knowledge_index_v1.jsonldata/runtime/jianghan_phase_context_v1.jsonldata/runtime/jianghan_stage3_runtime_policy_v1.md
RAG-only smoke test:
python scripts/jianghan_runtime_rag.py \
--prompt "猫灯和奥维利亚是什么关系?" \
--stage 第三阶段 \
--profile fact
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