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Yi-1.5-9B-Chat-16K-abliterated

byroneverson/Yi-1.5-9B-Chat-16K-abliterated

abliteratedfine-tuned
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About this model

byroneverson's abliterated derivative of 01-ai/Yi-1.5-9B-Chat-16K, provided as safetensors weights under the Apache-2.0 license. The model card states that this is an abliterated model with no finetuning, and the creator says it beats the original model on the LLM Leaderboard. A linked Jupyter notebook documents the abliteration process. The leaderboard comparison is creator-reported and has 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
01-ai/Yi-1.5-9B-Chat-16K
Parameters
8.82941B
Main repository formats
safetensors
License tag
apache-2.0
Languages
en, zh
Last updated
2024-09-06 · 21:15:34.000 UTC

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: Yi-1.5-9B-Chat-16K-abliterated
  • fine-tunedsource tag: base_model:finetune:01-ai/Yi-1.5-9B-Chat-16K

Family evidence

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

  • No supported family evidence recorded.

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/byroneverson-yi-1-5-9b-chat-16k-abliterated-2dcf2967701f/)

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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

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  • 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.

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    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.

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Source provenance

Downloads
8,533
Likes
4
Metadata checked
2026-10-24 · 16:13:40 UTC
First seen in index
2026-10-24 · 16:13:40 UTC
Source revision
44af9f183222b26a00dce938fac807e097654e1b

Source-card excerpt

Source model card excerpt: Yi-1.5-9B-Chat-16K-abliterated Note: This abliterated model (no finetuning) beats the original model on the LLM Leaderboard. Model Average IFEval BBH MATH Lvl 5 GPQA MUSR

From byroneverson/Yi-1.5-9B-Chat-16K-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 ↗