This repository contains a LoRA adapter fine-tuned on the state-of-the-art Qwen 3.5 9B architecture. It is designed to enhance character consistency, narrative depth, and uncensored dialogue in roleplay scenarios.

The adapter was trained using Unsloth for maximum efficiency on:

Base model: Qwen/Qwen3.5-9B
Intermediate model: techwithsergiu/Qwen3.5-text-9B

⚠️ This repository contains LoRA weights only. You must load these weights on top of the intermediate model for the best results.

Intended Use

This model is built for:

Advanced storytelling and character-driven roleplay.
Research into multimodal-capable foundation models (Qwen 3.5).
Experimentation with uncensored, expressive dialogue.

❌ Prohibited Use

Generation of content involving minors.
Non-consensual, exploitative, or illegal content.
Real-person sexual content (Deepfakes).
Professional advice (medical, legal, financial).

Ethical & Safety Notice

The user assumes all responsibility for the content generated. The model is fully uncensored and will not refuse requests. Please ensure your usage complies with your local laws and platform terms of service.

How to Use

For the best experience, use ChatML format as the training utilized this template to prevent "thinking" leaks and maintain immersion.

python

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
import torch

base_model_id = "techwithsergiu/Qwen3.5-text-9B"
lora_model_id = "mirazrafi/NSFW-RP-RolePlay-LoRA-Qwen-3.5-9B"

tokenizer = AutoTokenizer.from_pretrained(base_model_id)
model = AutoModelForCausalLM.from_pretrained(
    base_model_id, 
    torch_dtype=torch.float16, 
    device_map="auto"
)
model = PeftModel.from_pretrained(model, lora_model_id)

Training Details

Architecture: Qwen 3.5 (Hybrid Gated DeltaNet)
Method: LoRA (PEFT) with Rank-Stabilized LoRA (RS-LoRA)
Rank (r): 64
Alpha: 64
Target Modules: q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
Training Tool: Unsloth
Precision: 4-bit (bitsandbytes) / FP16

License

LoRA Adapter: Apache License 2.0
Base Model: Apache License 2.0
Intermediate Model: Apache License 2.0

Acknowledgements

Alibaba Cloud / Qwen Team – For the Qwen 3.5 foundation.
techwithsergiu – For the bnb variant of base model.
Unsloth AI – For the optimized training framework.