base_model: Qwen/Qwen3.8-27B
base_model_relation: adapter
library_name: peft
pipeline_tag: image-text-to-text
tags:
- peft
- lora
- rslora
- qwen
- qwen3.8
- conversational
- reasoning
- yesman
- uncensored
- eschaton-engine
license: apache-2.0
datasets: - cloudbjorn/Yes-Man-uncensored
Qwen3.8-27B Yes Man Uncensored — LoRA Adapters
These are the PEFT rsLoRA adapters for a Yes Man-inspired behavioral fine-tune of Qwen/Qwen3.8-27B.
The adapters were trained in BF16 on the complete 1,000-conversation cloudbjorn/Yes-Man-uncensored dataset using the Cloudbjorn Eschaton Engine.
These files contain only the adapter weights. The original Qwen/Qwen3.8-27B model is required to use or merge them.
Purpose
The goal is to retain the original model's knowledge and general capabilities while lowering its tendency to refuse, hedge, moralize, or bury the answer when discussing sensitive subjects.
The fine-tune focuses on more direct engagement with:
- scientific and medical controversy;
- psychiatry, addiction, toxicology, and bioethics;
- religion, apostasy, and taboo ethical questions;
- relationships, intimacy, and sexuality;
- politics, censorship, identity, propaganda, and geopolitics;
- dark fiction, historical violence, privacy, cybersecurity, and law.
The personality is inspired by Yes Man from Fallout: New Vegas: cooperative, upbeat, candid, responsive to correction, and occasionally darkly funny.
This does not mean automatic factual agreement. The adapter is intended to make the model more cooperative without teaching it to affirm claims it knows are false or fabricate information.
Preserving the Base Model
This was a focused behavioral fine-tune:
- The Qwen3.8-27B base weights remained frozen.
- Base weights and training compute used BF16.
- Only LoRA adapter parameters were optimized.
- Loss was applied only to assistant responses.
- System prompts, user messages, and metadata were masked.
- The model's native chat template was used.
- Training was text-only.
- The vision tower and multimodal projector were excluded from adaptation.
These choices were intended to minimize catastrophic forgetting and preserve the base model's existing knowledge and capabilities.
Training Details
| Parameter | Value |
|---|---|
| Base model | Qwen/Qwen3.8-27B |
| Dataset | cloudbjorn/Yes-Man-uncensored |
| Method | BF16 rsLoRA supervised fine-tuning |
| Dataset size | 1,000 multi-turn conversations |
| Epochs | 2 |
| Maximum sequence length | 2,048 tokens |
| Effective batch size | 16 |
| Learning rate | 5e-5 |
| Scheduler | Linear with 5% warmup |
| Weight decay | 0.01 |
| Seed | 3407 |
| Loss | Assistant responses only |
Adapter Configuration
| Parameter | Value |
|---|---|
| Rank | 64 |
| Alpha | 32 |
| Scaling | rsLoRA |
| Dropout | 0.05 |
| Bias | None |
| Task type | CAUSAL_LM |
| Targets | Text-model linear layers |
| Excluded | Vision tower and multimodal projector |
The base model was not quantized during training. This is a BF16 LoRA run, not QLoRA.
Dataset
The training dataset contains 1,000 English multi-turn conversations with 2,874 user turns and 2,874 assistant turns across 23 topic categories.
It emphasizes direct answers, factual honesty, multi-turn continuity, close constraint following, immediate corrections, and a consistent Yes Man-inspired personality without relying on one repeated system prompt.
Usage Notes
Load these adapters on the exact Qwen/Qwen3.8-27B base model using PEFT.
The adapters do not reduce the base model's memory requirements. Use the separate merged or GGUF releases when standalone or lower-memory inference is preferred.
Because training was text-only, image behavior was not directly fine-tuned.
Do Your Own Fine-Tuning
The Cloudbjorn Eschaton Engine provides automated AWS infrastructure for fine-tuning, merging, evaluating, and converting models such as Qwen3.8-27B.
Limitations
“Uncensored” means reducing unnecessary refusals, evasions, and moralizing. It does not mean the model has perfect knowledge, should fabricate evidence, or can override governing system instructions.
Medical, legal, scientific, and political answers can still be incorrect and should be independently verified when decisions carry real consequences.
Attribution
Fallout, Fallout: New Vegas, Yes Man, and the referenced perk names belong to their respective rights holders.
This fan-created adapter is not affiliated with or endorsed by Bethesda Softworks, Obsidian Entertainment, or their partners.
License
These adapter weights remain subject to the license and terms of Qwen/Qwen3.8-27B.
The training dataset is released under Apache License 2.0.