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failspy / Model details

Llama-3-8B-Instruct-abliterated

failspy/Llama-3-8B-Instruct-abliterated

abliterated
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About this model

This is failspy's refusal-modified derivative of meta-llama/Llama-3-8B-Instruct, provided as safetensors weights under the llama3 license. The creator describes the change as orthogonalizing out the strongest refusal direction from the bfloat16 weights, using a method based on the idea that refusal in LLMs is mediated by a single direction. According to the model card, the model is not guaranteed to stop refusing, may still lecture about ethics or safety, and is otherwise the same as the original 8B instruct model. The creator also notes the method is new and the model may have untested quirks. Refusal behavior and side effects have not been independently tested here.

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
Unknown
Parameters
8.03026B
Main repository formats
safetensors
License tag
llama3
Languages
Unknown
Last updated
2024-05-12 · 17:55:12.000 UTC

What changed

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

  • abliteratedmodel name: Llama-3-8B-Instruct-abliterated

Family evidence

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

  • Llama: Family / architecture tag: llama

Available versions

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

Link to this listing

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Markdown

[Listed on Custom Clankers](https://customclankers.com/models/failspy-llama-3-8b-instruct-abliterated-42fcb91ecf52/)

HTML

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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 ↗ ★ 36,365

    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 ↗ ★ 8,941

    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 ↗ ★ 78,505

    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 ↗ ★ 75,708

    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 ↗ ★ 132,209

    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 ↗ ★ 7,461

    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 ↗ ★ 84,653

    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
851
Likes
13
Metadata checked
2026-10-24 · 16:13:40 UTC
First seen in index
2026-10-24 · 16:13:40 UTC
Source revision
dd67dd055661e4cbcedb0ed2431693d9cc3be6e0

Source-card excerpt

Source model card excerpt: Llama-3-8B-Instruct-abliterated Model Card This is meta-llama/Llama-3-8B-Instruct with orthogonalized bfloat16 safetensor weights, generated with the methodology that was described in the preview paper/blog post: 'Refusal

From failspy/Llama-3-8B-Instruct-abliterated. 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 ↗