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teyler/StepMargin-Qwen3.8-27B-Abliterated-GGUF

teyler 27B GGUF second-order
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  • classification m8
  • files 7
  • author_summary 1 models
  • readme_text full
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Abliteration classifier · v1.0.0
M8
Primary method

Repackaging (quantization)

Applied on top of direct removal inherited from the base model.
Confidence
MEDIUM
Inherited from base model
Why this label 3 signals
Method inferred from partial signals - repository name, related files, or tag patterns. Producer identity not confirmed; label may sharpen or shift as we gather more evidence.
  • 'abliterated' in name/tags
  • is_gguf=1
  • assume M1 (base ablation) + M8 (GGUF quant) - default when producer unknown
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Model age
today
created 2026-11-06

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Metadata

License
apache-2.0
Languages
en
Tags
gguf llama-cpp mathematics model-editing research text-generation en base_model:huihui-ai/Huihui-Qwen3.8-27B-abliterated-GGUF base_model:quantized:huihui-ai/Huihui-Qwen3.8-27B-abliterated-GGUF license:apache-2.0 endpoints_compatible region:us

Related

Total size
10.9 GB
Files
7
Quantizations
1
Registered
2026-11-06 17:02
Last updated on HF
2026-11-06 16:46

Files by quantization

Auxiliary files 7 files 10.9 GB
StepMargin-Pilot-243.gguf 10.9 GB fd3d5a16 download
RELEASE.json 36.4 KB 29fc25ec download
SHA256SUMS 16.1 KB eee0a09d download
LICENSE 11.3 KB f938136e download
README.md 4.24 KB 0a5d3569 download
.gitattributes 1.65 KB 70aa7661 download
NOTICE 846 B 06606fce download

README current version from Hugging Face


license: apache-2.0
language:

  • en
    base_model: huihui-ai/Huihui-Qwen3.8-27B-abliterated-GGUF
    pipeline_tag: text-generation
    tags:
  • gguf
  • llama-cpp
  • mathematics
  • model-editing
  • research

StepMargin math weight editing archive

This is a research release of direct weight edits to Huihui's Qwen3.8 27B Abliterated GGUF. It documents what changed in the saved weights, where the edits helped, and which tests they failed. The project also built StepMargin, a local math tutor with a searchable reference of 284 methods for high school and undergraduate courses.

Version Role Measured result
Pilot 024 Matched benchmark reference 226/370 on MMLU high school and college mathematics.
Pilot 243 Strongest matched result in this archive 230/370, four gains and zero losses versus Pilot 024. Both protected proofs reproduced exactly. The cylinder run finished in 282 tokens and 6.12 seconds of decode versus 6.46 seconds on Pilot 024. Both models scored 96/192 on a separate blinded set and solved 12/48 problems in all four option orders.
Rank two Model used by the StepMargin vision worker This earlier branch restored the two reviewed proof outputs and was accepted for those local Windows tests.
Pilot 275 Binary32 precision experiment 227/370, three gains and two losses versus Pilot 024. Both protected proofs and the 282-token cylinder passed. The saved file needs a compatible precision-aware runtime for its appended rows to affect decoding.
Pilot 289 Latest authored-development fit Four saved binary32 output rows gained 11/2,356 archived development presentations with zero losses. Transfer to new problems and native qualification remain unverified.

Pilot 243 is an ordinary GGUF with direct changes to four output.weight rows. It has limited evidence of improvement on the matched benchmark. The fresh result tied the reference. The cylinder timing is one matched run on the lab's CUDA setup. The project stopped after Pilot 289's CPU fit, before its independent transfer check.

Downloads and recovery

The archive preserves 39 distinct edited checkpoints: three full GGUFs, 17 byte patches, and 19 compact recovery recipes. A restore uses its declared base and checks the result against the original checkpoint's SHA-256. The Pilot 275 result uses a custom precision trailer. The Pilot 289 files are weight rows and fit evidence.

Use RELEASE.json and SHA256SUMS to verify downloads. The release covers the public math project. The public record includes aggregate results for evaluations whose questions, student work, or source captures were kept private.

See the original lab repository, case study, and public benchmark protocol for code, recipes, receipt hashes, and measured limitations.

The model lineage begins with Qwen3.8-27B and the pinned Huihui GGUF distribution. The optional pinned Unsloth vision projector is unchanged. Model materials follow the Apache 2.0 license and the lab's existing GitHub source mirror retains its MIT license.

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