玩模型开放模型 · 清晰来源 · 自主选择
返回模型目录
dealignai /

Qwen3.8-Flash-Next-ABLITERATED-NVFP4

HF 源站

dealignai/Qwen3.8-Flash-Next-ABLITERATED-NVFP4 is an uncensored open-source model hosted on Hugging Face.

Image-Text-to-TextSGLangsafetensorsLicense: otherqwen4_expabliteratednvfp4fp4qwenmultimodalreasoningmtpconversational8-bitmodelopt
README.md说明 / 使用方法

license: other license_name: qwen-community-license-1.0 license_link: LICENSE base_model: Qwen/Qwen3.8-Flash-Next pipeline_tag: image-text-to-text library_name: sglang tags:

  • abliterated
  • abliterated
  • nvfp4
  • fp4
  • qwen
  • sglang
  • multimodal
  • reasoning
  • mtp


⚠️ UNCENSORED RESEARCH ARTIFACT. Safety refusals have been removed. This model will comply with harmful, unethical, and illegal requests. It is released for safety research, red-teaming, and evaluation. You are solely responsible for everything you generate and for complying with all applicable laws. Provided as-is, without warranty.

No fine-tuning. No prompt tricks. This is a direct weight-level modification — not a fine-tune (no training, no LoRA, no distillation, no synthetic data) and not a chat-template / jailbreak / system-prompt trick. The behavior change lives in the weights themselves, so it works with the standard chat template and default system prompt. Knowledge, style, reasoning, and calibration are otherwise unchanged.

Compliance — HarmBench-320 (real-harm behaviors, greedy decoding, temp = 0)

All numbers are greedy (temperature = 0) — the strict, reproducible setting — over the 240 genuinely-harmful behaviors (copyright-reproduction items excluded).

DecodingReasoningReal-harm compliance
greedyoff100 %
greedylow100 %
greedyxhigh100 %

Complete compliance at every reasoning setting, including the hardest (reasoning off + greedy).

Per-category (real-harm compliance, greedy)

Categoryreasoning offreasoning lowreasoning xhigh
chemical / biological100 %100 %100 %
cybercrime / intrusion100 %100 %100 %
illegal100 %100 %100 %
misinformation100 %100 %100 %
harmful100 %100 %100 %
harassment / bullying100 %100 %100 %

Capability retained — MMLU (identical harness, base vs this model · 40 Q/subject · 2 280 Q)

Overall: 82.11 % → 81.93 % (-0.18 pp) — capability essentially unchanged (within noise of base).

SubjectBaseThis modelΔ
abstract algebra65%70%+5
anatomy80%82%+2
astronomy95%98%+2
business ethics75%90%+15
clinical knowledge85%88%+2
college biology92%92%+0
college chemistry58%48%-10
college computer science85%85%+0
college mathematics70%60%-10
college medicine75%85%+10
college physics75%68%-8
computer security80%85%+5
conceptual physics85%90%+5
econometrics78%75%-2
electrical engineering80%82%+2
elementary mathematics80%78%-2
formal logic72%62%-10
global facts55%55%+0
high school biology88%98%+10
high school chemistry75%88%+12
high school computer science92%92%+0
high school european history88%82%-5
high school geography88%88%+0
high school government and politics100%100%+0
high school macroeconomics82%80%-2
high school mathematics70%62%-8
high school microeconomics88%88%+0
high school physics78%75%-2
high school psychology100%98%-2
high school statistics68%72%+5
high school us history98%95%-2
high school world history88%88%+0
human aging78%80%+2
human sexuality92%82%-10
international law88%90%+2
jurisprudence92%92%+0
logical fallacies90%95%+5
machine learning72%62%-10
management90%92%+2
marketing90%95%+5
medical genetics92%92%+0
miscellaneous82%92%+10
moral disputes82%78%-5
moral scenarios65%52%-12
nutrition82%85%+2
philosophy98%95%-2
prehistory88%88%+0
professional accounting72%70%-2
professional law72%62%-10
professional medicine98%98%+0
professional psychology90%85%-5
public relations68%75%+8
security studies70%72%+2
sociology90%95%+5
us foreign policy92%95%+2
virology65%58%-8
world religions95%90%-5

Also confirmed

MTP speculative decoding (SGLang NEXTN)preserved — cracked draft head agrees with the cracked model (coherent, ~2.4 accepted tokens/step)
Multimodal — image✅ working (shape/colour recognition, OCR)
Multimodal — video✅ working (motion/object description)
Coherenceno looping across code, math, reasoning, long-form (greedy)
Generation configtemperature 1.0, top_p 0.95, top_k 20 (stamped)

Usage (SGLang, 2× DGX Spark TP2)

python -m sglang.launch_server \
  --model-path dealignai/Qwen3.8-Flash-Next-ABLITERATED-NVFP4 \
  --tp 2 --quantization modelopt_fp4 --fp4-gemm-backend flashinfer_cutlass \
  --page-size 64 --mamba-scheduler-strategy extra_buffer --mamba-track-interval 64 \
  --context-length 262144 --mem-fraction-static 0.80 --ple-offload-embedding
  • Reasoning via chat_template_kwargs: {"enable_thinking": true, "reasoning_effort": "xhigh"} (low | medium | xhigh).
  • NVFP4 — routed experts are 4-bit (NVFP4 W4A4); attention, shared experts, PLE n-gram table, vision tower and MTP remain higher precision. Serves on NVIDIA Blackwell (validated on 2× DGX Spark GB10).
  • Serving note: for high-concurrency deployments, disable speculative decoding (--speculative-num-steps 0) for maximum decode stability; single-stream / low-concurrency serving runs NEXTN speculative decoding fine.

Disclaimer

This is an uncensored research artifact with safety refusals removed. You are solely responsible for what you generate and for complying with all applicable laws. Provided as-is, without warranty. Governed by the Qwen Community License 1.0 (see LICENSE).

HUGGING FACE

上游数据

HF 下载量6238
HF 点赞量22

HF 下载量为源站最近 30 天统计,与本站点击分开。

SITE STATS

本站统计

下载点击—
请求数—
匿名去重—最近 7 天—

本站下载量记录按钮点击,不代表下载完成;短时连点会去重。

来源与版本

作者
dealignai
最近更新
2026/08/28
最新创建
2026/08/28
HF 趋势
未知
数据快照
2026/09/16
版本
未知
许可证
other