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tensorblock/Josiefied-Qwen2.5-14B-Instruct-abliterated-v4-GGUF

tensorblock Qwen 14B GGUF second-order 33K ctx
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curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/tensorblock%2FJosiefied-Qwen2.5-14B-Instruct-abliterated-v4-GGUF"
Response includes
  • classification m8
  • files 4
  • benchmarks 5 entries
  • hub_downloads_all_time 2,800
  • 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='Goekdeniz-Guelmez/Josiefied-Qwen2.5-14B-Instruct-abliterated-v4' 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
3K
67 last 30d - cooling
Likes
0
Model age
22mo ago
created 2024-11-27
Downloads over time
Now2.8K→from300↑840%
01K2.1K3.1K300 on Nov 27, 20242.8K on Oct 11Nov '24Feb '25May '25Aug '25Nov '25FebMayAug
Nov 27, 2024 → Oct 11 · 137 snapshots · spans 683 days

Benchmarks

Benchmark Score Source
BBH average 0.5680373589311195 OpenLLM-v2
IFEval instruct 0.8561151079136691 OpenLLM-v2
IFEval-Prompt 0.8022181146025879 OpenLLM-v2
MATH lvl 5 0 OpenLLM-v2
MMLU-Pro 0.5018284574468085 OpenLLM-v2

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 de
Quantizations
Q2_K Q3_K
Tags
gguf chat TensorBlock GGUF text-generation en de base_model:Goekdeniz-Guelmez/Josiefied-Qwen2.5-14B-Instruct-abliterated-v4 base_model:quantized:Goekdeniz-Guelmez/Josiefied-Qwen2.5-14B-Instruct-abliterated-v4 license:apache-2.0 model-index endpoints_compatible

Related

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

Files by quantization

Q3_K 1 file 6.84 GB
Josiefied-Qwen2.5-14B-Instruct-abliterated-v4-Q3_K_M.gguf 6.84 GB eaf2d21f download
Q2_K 1 file 5.37 GB
Josiefied-Qwen2.5-14B-Instruct-abliterated-v4-Q2_K.gguf 5.37 GB 86aa89d5 download
Auxiliary files 2 files 13.1 KB
README.md 10.5 KB 8ada0e4b download
.gitattributes 2.58 KB 491ae626 download

README current version from Hugging Face


language:


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Goekdeniz-Guelmez/Josiefied-Qwen2.5-14B-Instruct-abliterated-v4 - GGUF

This repo contains GGUF format model files for Goekdeniz-Guelmez/Josiefied-Qwen2.5-14B-Instruct-abliterated-v4.

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
Josiefied-Qwen2.5-14B-Instruct-abliterated-v4-Q2_K.gguf Q2_K 5.770 GB smallest, significant quality loss - not recommended for most purposes
Josiefied-Qwen2.5-14B-Instruct-abliterated-v4-Q3_K_S.gguf Q3_K_S 6.660 GB very small, high quality loss
Josiefied-Qwen2.5-14B-Instruct-abliterated-v4-Q3_K_M.gguf Q3_K_M 7.339 GB very small, high quality loss
Josiefied-Qwen2.5-14B-Instruct-abliterated-v4-Q3_K_L.gguf Q3_K_L 7.925 GB small, substantial quality loss
Josiefied-Qwen2.5-14B-Instruct-abliterated-v4-Q4_0.gguf Q4_0 8.518 GB legacy; small, very high quality loss - prefer using Q3_K_M
Josiefied-Qwen2.5-14B-Instruct-abliterated-v4-Q4_K_S.gguf Q4_K_S 8.573 GB small, greater quality loss
Josiefied-Qwen2.5-14B-Instruct-abliterated-v4-Q4_K_M.gguf Q4_K_M 8.988 GB medium, balanced quality - recommended
Josiefied-Qwen2.5-14B-Instruct-abliterated-v4-Q5_0.gguf Q5_0 10.267 GB legacy; medium, balanced quality - prefer using Q4_K_M
Josiefied-Qwen2.5-14B-Instruct-abliterated-v4-Q5_K_S.gguf Q5_K_S 10.267 GB large, low quality loss - recommended
Josiefied-Qwen2.5-14B-Instruct-abliterated-v4-Q5_K_M.gguf Q5_K_M 10.509 GB large, very low quality loss - recommended
Josiefied-Qwen2.5-14B-Instruct-abliterated-v4-Q6_K.gguf Q6_K 12.125 GB very large, extremely low quality loss
Josiefied-Qwen2.5-14B-Instruct-abliterated-v4-Q8_0.gguf Q8_0 15.702 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/Josiefied-Qwen2.5-14B-Instruct-abliterated-v4-GGUF --include "Josiefied-Qwen2.5-14B-Instruct-abliterated-v4-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/Josiefied-Qwen2.5-14B-Instruct-abliterated-v4-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. 2025-07-09Update README.mdbd4841a10.5 KB
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  2. 2025-06-19Update README.md778cc1e9.8 KB
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  3. 2025-04-20Update README.md38200fe9.7 KB
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  4. 2024-11-27Upload folder using huggingface_hub214ad0e8.8 KB
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