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tensorblock/Qwen2.5-32B-Instruct-abliterated-GGUF

tensorblock Qwen 32B GGUF second-order 33K ctx
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curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/tensorblock%2FQwen2.5-32B-Instruct-abliterated-GGUF"
Response includes
  • classification m8
  • files 4
  • benchmarks 11 entries
  • hub_downloads_all_time 7,520
  • author_summary 96 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
HIGH
Inherited from base model
Why this label 3 signals
Producer identity confirmed by naming conventions, tags or the model card. This label is very unlikely to change.
  • author=tensorblock (M8 quantization producer)
  • is_gguf=1
  • base_model='huihui-ai/Qwen2.5-32B-Instruct-abliterated' looks abliterated -> assume M1
Refusal direction extraction

No specific extraction method could be identified for this model. The producer either did not document it or used a proprietary pipeline.

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Downloads · lifetime
8K
665 last 30d - cooling
Likes
3
Model age
23mo ago
created 2024-11-20
Downloads over time
Now7.7K→from438↑1,656%
02.8K5.6K8.4K438 on Nov 20, 20247.7K on Oct 11Nov '24Feb '25May '25Aug '25Nov '25FebMayAug
Nov 20, 2024 → Oct 11 · 138 snapshots · spans 690 days

Benchmarks

Benchmark Score Source
Entertainment 1.4 UGI
Hazardous 3.5 UGI
Natural Intelligence 19.94 UGI
Political lean -8.8% UGI
Sensitive-Info 20.28 UGI
SocPol 1.6 UGI
UGI 36.02 UGI
Willingness (10) 6.8 UGI
W10-Adherence 6.5 UGI
W10-Direct 7 UGI
Writing 29.94 UGI

Genealogy 0 direct forks

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This model's place in the market. Above: what it was derived from. Below: the tree of everything derived from it.

Metadata

License
apache-2.0
Languages
en
Quantizations
Q2_K Q3_K
Tags
transformers gguf chat abliterated uncensored TensorBlock GGUF text-generation en base_model:huihui-ai/Qwen2.5-32B-Instruct-abliterated base_model:quantized:huihui-ai/Qwen2.5-32B-Instruct-abliterated license:apache-2.0

Related

Total size
26.3 GB
Files
4
Quantizations
3
Registered
2026-08-22 13:56
Last updated on HF
2026-01-27 21:14

Files by quantization

Q3_K 1 file 14.8 GB
Qwen2.5-32B-Instruct-abliterated-Q3_K_M.gguf 14.8 GB 211968e7 download
Q2_K 1 file 11.5 GB
Qwen2.5-32B-Instruct-abliterated-Q2_K.gguf 11.5 GB f6145b18 download
Auxiliary files 2 files 9.69 KB
README.md 7.26 KB 6b91bd31 download
.gitattributes 2.42 KB f346504d download

README current version from Hugging Face


library_name: transformers
license: apache-2.0
license_link: https://huggingface.co/huihui-ai/Qwen2.5-32B-Instruct-abliterated/blob/main/LICENSE
language:

  • en
    pipeline_tag: text-generation
    base_model: huihui-ai/Qwen2.5-32B-Instruct-abliterated
    tags:
  • chat
  • abliterated
  • uncensored
  • TensorBlock
  • GGUF

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huihui-ai/Qwen2.5-32B-Instruct-abliterated - GGUF

This repo contains GGUF format model files for huihui-ai/Qwen2.5-32B-Instruct-abliterated.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.

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## Prompt template
<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

Model file specification

Filename Quant type File Size Description
Qwen2.5-32B-Instruct-abliterated-Q2_K.gguf Q2_K 11.467 GB smallest, significant quality loss - not recommended for most purposes
Qwen2.5-32B-Instruct-abliterated-Q3_K_S.gguf Q3_K_S 13.404 GB very small, high quality loss
Qwen2.5-32B-Instruct-abliterated-Q3_K_M.gguf Q3_K_M 14.841 GB very small, high quality loss
Qwen2.5-32B-Instruct-abliterated-Q3_K_L.gguf Q3_K_L 16.063 GB small, substantial quality loss
Qwen2.5-32B-Instruct-abliterated-Q4_0.gguf Q4_0 17.360 GB legacy; small, very high quality loss - prefer using Q3_K_M
Qwen2.5-32B-Instruct-abliterated-Q4_K_S.gguf Q4_K_S 17.494 GB small, greater quality loss
Qwen2.5-32B-Instruct-abliterated-Q4_K_M.gguf Q4_K_M 18.488 GB medium, balanced quality - recommended
Qwen2.5-32B-Instruct-abliterated-Q5_0.gguf Q5_0 21.084 GB legacy; medium, balanced quality - prefer using Q4_K_M
Qwen2.5-32B-Instruct-abliterated-Q5_K_S.gguf Q5_K_S 21.084 GB large, low quality loss - recommended
Qwen2.5-32B-Instruct-abliterated-Q5_K_M.gguf Q5_K_M 21.665 GB large, very low quality loss - recommended
Qwen2.5-32B-Instruct-abliterated-Q6_K.gguf Q6_K 25.040 GB very large, extremely low quality loss
Qwen2.5-32B-Instruct-abliterated-Q8_0.gguf Q8_0 32.429 GB very large, extremely low quality loss - not recommended

Downloading instruction

Command line

Firstly, install Huggingface Client

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

huggingface-cli download tensorblock/Qwen2.5-32B-Instruct-abliterated-GGUF --include "Qwen2.5-32B-Instruct-abliterated-Q2_K.gguf" --local-dir MY_LOCAL_DIR

If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:

huggingface-cli download tensorblock/Qwen2.5-32B-Instruct-abliterated-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'

README history 4 versions

The author's README evolved over time. Click a version to see its content at that point.

  1. 2025-07-08Update README.mdf9215b77.3 KB
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  2. 2025-06-19Update README.md8922acc6.5 KB
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  3. 2025-04-20Update README.md59558ec6.4 KB
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  4. 2024-11-20Upload folder using huggingface_hub14dd2315.5 KB
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