Qwen3.8-27B-LoRA — Collection of LoRA Adapters

NOESIS / AMAImedia

Last updated: 2026-08-30

Released as part of the NOESIS Professional Multilingual Dubbing Automation Platform (framework: DHCF-FNO — Deterministic Hybrid Control Framework for Frozen Neural Operators).

• Founder: Ilia Bolotnikov
• Organization: AMAImedia.com
• X (Twitter): @AMAImediacom
• LinkedIn: Ilia Bolotnikov
• Telegram: @djbionicl
• Release date: 2026-08-30

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Collection: AMAImedia/hy4-glm53-kimik3-deepseek4-qwen38 Base model: Qwen3.8-27B (27B params, BF16)

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What is this

A collection of 12 LoRA adapters for Qwen3.8-27B, covering various domains:

• Uncensored/abliterated models
• Style adapters (Steiner, Vernunft, Samantha)
• Domain-specific (Finance, Turkish, SNES gaming)
• Multi-task (Jurilix legal, Cyber, Huihui-Cyber)

Each adapter is in its own subfolder with original source links.

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LoRA Adapters

1. Synergetic

Path: Synergetic/ Source: TheMindExpansionNetwork/MindBot-Qwen3.8-27B-Synergetic-LoRA Description: Synergetic thinking adapter — enhances coordinated multi-step reasoning and collaborative problem-solving. Size: ~325 MB

2. Yes-Man Uncensored

Path: Yes-Man/ Source: cloudbjorn/Qwen3.8-27B-Yes-Man-uncensored-LoRA Description: Uncensored compliance adapter — removes refusals and enables unrestricted responses. Size: ~974 MB

3. Finance

Path: Finance/ Source: nico248000000000/Qwen3.8-27B-finance-LoRA Description: Finance domain adapter — enhances financial analysis, market understanding, and economic reasoning. Size: ~188 MB

4. SNES Retro Gaming

Path: SNES/ Source: pottokao/SNES-LoRA-Qwen3.8-27B Description: SNES/retro gaming knowledge adapter — game mechanics, retro gaming culture, pixel art. Size: ~608 MB

5. Huihui Cyber

Path: Huihui-Cyber/ Source: nico248000000000/Huihui-Qwen3.8-27B-abliterated-cyber-LoRA Description: Abliterated cyber adapter — combines uncensored behavior with cyberpunk/tech aesthetics. Size: ~188 MB

6. Samantha Uncensored

Path: Samantha/ Source: Lathly/Qwen3.8-27B-Samantha_Uncensored_1.1_LoRA Description: Samantha personality adapter v1.1 — uncensored conversational AI with personality traits. Size: ~475 MB

7. Cyber

Path: Cyber/ Source: nico248000000000/Qwen3.8-27B-cyber-LoRA Description: Cyber domain adapter — technology, cybersecurity, hacking concepts, digital systems. Size: ~188 MB

8. Turkish CPT

Path: Turkish/ Source: UgurI/Qwen3.8-27B-Turkish-CPT-LoRA-Beta Description: Turkish language Continual Pre-Training adapter — enhances Turkish language understanding and generation. Size: ~304 MB

9. Fable Distill

Path: Fable-Distill/ Source: TeichAI/Qwen3.8-27B-Fable-Distill-LoRA Description: Fable distillation adapter — storytelling, narrative generation, creative writing. Size: ~910 MB

10. Jurilix Multi-Task Legal

Path: Jurilix/ Source: Makio64/Qwen3.8-27B-jurilix-multitache-lora Description: Multi-task legal adapter — legal document analysis, contract review, legal reasoning. Size: ~353 MB

11. Steiner Style

Path: Steiner/ Source: ericlmtn/Qwen3.8-27B-Steiner-Style-LoRA Description: Steiner-style adapter — anthroposophical perspective, holistic thinking, Waldorf education approach. Size: ~445 MB

12. Vernunft (Reasoning)

Path: Vernunft/ Source: schneewolflabs/Vernunft-Qwen3.8-27B-LoRA Description: Reasoning adapter (Vernunft = German for "reason") — enhanced logical reasoning and analytical thinking. Size: ~627 MB

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Usage

With transformers

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel

# Load base model
base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.8-27B")
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3.8-27B")

# Load LoRA adapter
model = PeftModel.from_pretrained(base_model, "AMAImedia/Qwen3.8-27B-LoRA/Synergetic")

# Generate
inputs = tokenizer("Hello, how are you?", return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=100)
print(tokenizer.decode(outputs[0]))

With mlx-lm (Apple Silicon)

pip install mlx-lm

# Merge LoRA into base model
mlx_lm.lora --model Qwen/Qwen3.8-27B --adapter-path ./Synergetic --output ./merged

With llama.cpp

# Convert to GGUF first
python convert_hf_to_gguf.py ./merged --outfile model.gguf --outtype f16

# Run inference
llama-cli -m model.gguf -p "Hello, how are you?" -n 100

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License

Each adapter inherits the license of its source repository. Most are Apache-2.0 or MIT.

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Acknowledgments

Thanks to all the original creators of these LoRA adapters. This collection aggregates them for easy access and comparison.

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Collected and organized by AMAImedia, 2026-08-30