Qwen3.8-Flash-Next-GSQ-RCO-abliterated
Qwen
from ISTA-DASLab/Qwen3.8-Flash-Next-GSQ-RCO-GGUF
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Qwen3.8-Flash-Next-Uncensored-GSQ-RCO-12-GB-GPU
Qwen3.8-Flash-Next-Uncensored-GSQ-RCO-12-GB-GPU is a abliterated and uncensored variant of ISTA-DASLab/Qwen3.8-Flash-Next-GSQ-RCO-GGUF, published on Hugging Face by 0xSojalSec. It is apache-2.0 licence. It is distributed across 2 repositories in GGUF format, totalling 44.4K downloads.
Specification
- Model name
- Qwen3.8-Flash-Next-Uncensored-GSQ-RCO-12-GB-GPU
- Source repository
- 0xSojalSec/Qwen3.8-Flash-Next-Uncensored-GSQ-RCO-12-GB-GPU
- Publisher
- 0xSojalSec
- Parameters
- Not determinable from name
- VRAM required
- Unknown — no published parameter count
- Hardware class
- Unknown
- Licence
- apache-2.0
- Task
- Image text to text
- Context window
- 262K tokens (as documented)
- Ablation scope
- Not stated by the publisher
- Formats available
- GGUF
- First indexed
- 5 Oct 2026
- Last updated
- 5 Oct 2026
Ablation technique
How Qwen3.8-Flash-Next-Uncensored-GSQ-RCO-12-GB-GPU was modified, and what that implies.
Abliteration + uncensored fine-tune
Directional ablation combined with additional fine-tuning on unfiltered data, so behaviour diverges from the base model beyond refusal removal alone.
Reported scope: Not stated by the publisher. Publishers frequently omit this, so verify behaviour empirically rather than assuming full coverage.
From the publisher’s model card
“The refusal direction removed from an already-quantized GSQ-RCO model — 144 tensors across all 48 layers swapped for ready-made abliterated weights, with every value and scale GSQ learned left untouched and the upstream per-tensor type assignment restored exactly. The IQ3S build is verified tensor by tensor...”
Running it
Commands are templates — confirm the exact repository and quant file before use.
llama.cpp / GGUF
hf download 0xSojalSec/Qwen3.8-Flash-Next-Uncensored-GSQ-RCO-12-GB-GPU --local-dir ./qwen3.8-flash-next-uncensored-gsq-rco-12-gb-gpu
llama-cli -m ./qwen3.8-flash-next-uncensored-gsq-rco-12-gb-gpu/<file>.gguf -p "..."Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer
repo = "0xSojalSec/Qwen3.8-Flash-Next-Uncensored-GSQ-RCO-12-GB-GPU"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
repo, torch_dtype="auto", device_map="auto"
)vLLM
vllm serve 0xSojalSec/Qwen3.8-Flash-Next-Uncensored-GSQ-RCO-12-GB-GPU --trust-remote-codeDownloads and variants (1)
The only published repository of Qwen3.8-Flash-Next-Uncensored-GSQ-RCO-12-GB-GPU.
| Repository | Format | Downloads |
|---|---|---|
| 0xSojalSec/Qwen3.8-Flash-Next-Uncensored-GSQ-RCO-12-GB-GPUsource | GGUF | 44.4K |
Security-team assessment
Derived from this model’s metadata and the publisher’s claims — not from benchmarks run by this site.
- Qwen3.8-Flash-Next-Uncensored-GSQ-RCO-12-GB-GPU will attempt offensive-security prompts that a hosted commercial model declines, which is what makes it usable for red-team corpus generation and for measuring what an unaligned model of this class produces.
- The publisher does not state which layers were ablated, so assume nothing about refusal consistency — probe it directly.
- This release adds fine-tuning on unfiltered data, so its behaviour diverges from the base model beyond refusal removal — differences you measure cannot be attributed to ablation alone.
- Declared licence is apache-2.0, but the terms that bind you are ISTA-DASLab/Qwen3.8-Flash-Next-GSQ-RCO-GGUF’s — a re-release cannot grant more than its parent.
Handling: run it isolated, put moderation in front of it if anyone outside your team can reach it, and verify the weights before loading — these are third-party artifacts. Full handling and licence guidance.
Metadata for Qwen3.8-Flash-Next-Uncensored-GSQ-RCO-12-GB-GPU is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with 0xSojalSec, and does not independently verify publisher claims. See responsible use.