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RVN-Qwen3.8-Flash-Next-Abliterated-Uncensored

0bserverx/RVN-Qwen3.8-Flash-Next-Abliterated-Uncensored

abliterateduncensoredfine-tuned
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About this model

RVN is a Qwen3.8-Flash-Next derivative for studying refusal behavior. It combines an embedding-preserving refusal-direction edit with a small LoRA repair trained on responses from the official base. This repository contains the text checkpoint only, without the original vision tower or MTP draft tensors. The creator reports reduced refusals, but explicitly limits capability-retention claims to the tasks and configurations tested.

Description sources

Source-based description, not an independent evaluation. Check the linked sources for the creator’s claims and limitations.

Size and formats

Base model
Qwen/Qwen3.8-Flash-Next
Parameters
176.944B
Main repository formats
safetensors
License tag
other
Languages
Unknown
Last updated
2026-09-01 · 02:57:15.000 UTC

Model announcements

Source-linked paraphrases of sampled community sources, not independently tested by this directory.

Sample window: to · 1 unique source link. This is a selected sample, not all community discussions.

Small sample: source links are not a count of independent reviewers or evidence of consensus.

Sources checked:

What changed

Model types are creator-reported, not independently tested. These labels describe source metadata, not a guarantee of behavior.

  • abliteratedsource tag: abliterated
  • abliteratedmodel name: RVN-Qwen3.8-Flash-Next-Abliterated-Uncensored
  • uncensoredsource tag: uncensored
  • uncensoredmodel name: RVN-Qwen3.8-Flash-Next-Abliterated-Uncensored
  • fine-tunedsource tag: base_model:finetune:Qwen/Qwen3.8-Flash-Next

Family evidence

These groupings are source-reported. Explicit base identifiers take priority over generic architecture tags.

  • Qwen: Base model: Qwen/Qwen3.8-Flash-Next

Available versions

Versions appear here only when they explicitly name this exact model as their source. Check each repository for available files.

Refusal profile

Not yet measured: larger than our runner handles (v1 limit 35 GB).

How we measure

Link to this listing

Made or quantized this model? Paste one of these into your model card or README so people can find this listing.

Markdown

[Listed on Custom Clankers](https://customclankers.com/models/0bserverx-rvn-qwen3-8-flash-next-abliterated-uncensored/)

HTML

<a href="https://customclankers.com/models/0bserverx-rvn-qwen3-8-flash-next-abliterated-uncensored/">Listed on Custom Clankers</a>

Plain text links only: no image, no script, nothing loaded from this site.

Customize or build on this model

Listed from public GitHub data, not tested by us. Read the code and license before you run anything.

Tools to customize it further

Remove more refusals

  • Heretic ↗ ★ 36,421

    Removes refusal behavior from transformer models automatically. It pairs directional ablation (abliteration) with an Optuna parameter search that tries to cut refusals while keeping the model close to the original, so you don't have to pick layers by hand.

  • OBLITERATUS ↗ ★ 8,946

    A larger refusal-removal toolkit with several abliteration methods, usable locally or through a hosted Hugging Face Space. Check the telemetry setting before you run it: the README describes telemetry as opt-in, but on by default in the Spaces version.

Fine-tune it on your own data

  • Unsloth ↗ ★ 78,528

    A desktop app and Python library for running and training models locally. Its README lists LoRA, QLoRA, full fine-tuning, DPO and GRPO, plus export to formats including GGUF, on Windows, Linux, WSL and macOS.

  • LlamaFactory ↗ ★ 75,713

    Fine-tunes more than 100 language and vision-language models from a command line or a browser-based Web UI, aimed at training without writing code.

Make a smaller download (quantize)

  • llama.cpp ↗ ★ 132,260

    Runs models locally and includes the tools behind most GGUF files. A conversion script turns Hugging Face weights into GGUF, and llama-quantize shrinks a high-precision GGUF to lower-bit formats, which can cost some accuracy.

  • MLX LM ↗ ★ 7,467

    Apple's MLX package for running and fine-tuning models on Apple silicon. It can quantize models and upload them to the Hugging Face Hub, and supports LoRA and full fine-tuning.

Merge it with another model

  • mergekit ↗ ★ 7,414

    Merges pretrained models with many merge methods. It works out-of-core, so merges can run on a CPU or with as little as 8 GB of VRAM, and it also handles LoRA extraction and mixture-of-experts merges.

Learn the techniques

  • LLM Course ↗ ★ 84,667

    A free course with roadmaps and Colab notebooks. Its notebooks include one-click tools for merging with MergeKit, quantizing to GGUF, GPTQ, EXL2, AWQ and HQQ, and automatic abliteration with custom datasets.

Compare all tools →

Source provenance

Downloads
583
Likes
12
Metadata checked
2026-10-25 · 05:05:23 UTC
First seen in index
2026-10-20 · 21:59:08 UTC
Source revision
38b6e951065008472ebfb72d1736c9df64bb0e9a

Source-card excerpt

Source model card excerpt: RVN Qwen3.8-Flash-Next Abliterated Uncensored A heavily abliterated derivative built only from the official Qwen3.8-Flash-Next checkpoint, with a measured 2% strict refusal rate ( 2/100

From 0bserverx/RVN-Qwen3.8-Flash-Next-Abliterated-Uncensored. Creator model-card excerpt, not an independent review.

Inspect before you run

Low refusal is not proof of correctness. Outputs can be inaccurate, harmful, or biased. Review the model card, license and files yourself. A license tag is not commercial-use advice. Parameter counts are source metadata; no hardware compatibility is implied.

This directory does not host or redistribute model weights. Refusal profiles are measured by us on a fixed prompt set; all other behavior claims are source-reported.

Collection rules & limitations ↗