← back to catalog · registered 2026-08-22 13:56

mradermacher/Qwen2.5-7b-nerd-uncensored-MFANN-slerp-GGUF

mradermacher Qwen 7B GGUF second-order 33K ctx
Your rig guess connected
? Why do I need an app?
Reading your rig…

This is a rough estimate. Install the free app - we'll show exact numbers.

Reading real hardware from your app right now. Numbers below are exact.

Below is the per-quantization compatibility for this model.

curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/mradermacher%2FQwen2.5-7b-nerd-uncensored-MFANN-slerp-GGUF"
Response includes
  • classification m8
  • files 14
  • benchmarks 5 entries
  • hub_downloads_all_time 1,808
  • author_summary 3324 models
  • readme_text full
10 credits · hourly refresh · ~4 KB payload Get an API key →
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=mradermacher (M8 quantization producer, never originator)
  • is_gguf=1
  • base_model='netcat420/Qwen2.5-7b-nerd-uncensored-MFANN-slerp' (base has 'abliterated' marker, assume M1 default)
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.

What is a refusal direction? →
Downloads · lifetime
2K
366 last 30d - stable
Likes
0
Model age
20mo ago
created 2025-01-25
Downloads over time
Now1.9K→from298↑544%
2178391.5K2.1K298 on Jan 22, 20251.9K on Oct 11Jan '25Apr '25Jul '25Oct '25JanAprJulOct
Jan 22, 2025 → Oct 11 · 129 snapshots · spans 627 days

Benchmarks

Benchmark Score Source
BBH average 0.2929043974575172 OpenLLM-v2
IFEval instruct 0.2038369304556355 OpenLLM-v2
IFEval-Prompt 0.10905730129390019 OpenLLM-v2
MATH lvl 5 0 OpenLLM-v2
MMLU-Pro 0.11003989361702128 OpenLLM-v2

Genealogy 0 direct forks

Full fork graph →

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

Metadata

Languages
en
Quantizations
F16 IQ4 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf mergekit merge en base_model:netcat420/Qwen2.5-7b-nerd-uncensored-MFANN-slerp base_model:quantized:netcat420/Qwen2.5-7b-nerd-uncensored-MFANN-slerp endpoints_compatible region:us conversational

Related

Total size
63.5 GB
Files
14
Quantizations
9
Registered
2026-08-22 13:56
Last updated on HF
2025-01-25 13:30

Files by quantization

F16 1 file 14.2 GB
Qwen2.5-7b-nerd-uncensored-MFANN-slerp.f16.gguf 14.2 GB 2b12fc90 download
Q8_0 1 file 7.54 GB
Qwen2.5-7b-nerd-uncensored-MFANN-slerp.Q8_0.gguf 7.54 GB ac6db9dd download
Q6_K 1 file 5.82 GB
Qwen2.5-7b-nerd-uncensored-MFANN-slerp.Q6_K.gguf 5.82 GB 7d9716b2 download
Q5_K 2 files 10.0 GB
Qwen2.5-7b-nerd-uncensored-MFANN-slerp.Q5_K_M.gguf 5.07 GB f28b98fa download
Qwen2.5-7b-nerd-uncensored-MFANN-slerp.Q5_K_S.gguf 4.95 GB cc521293 download
Q4_K 2 files 8.51 GB
Qwen2.5-7b-nerd-uncensored-MFANN-slerp.Q4_K_M.gguf 4.36 GB 95b4d00a download
Qwen2.5-7b-nerd-uncensored-MFANN-slerp.Q4_K_S.gguf 4.15 GB 2d0491f0 download
IQ4 1 file 3.96 GB
Qwen2.5-7b-nerd-uncensored-MFANN-slerp.IQ4_XS.gguf 3.96 GB 1d0ffe75 download
Q3_K 3 files 10.6 GB
Qwen2.5-7b-nerd-uncensored-MFANN-slerp.Q3_K_L.gguf 3.81 GB 7dba7aeb download
Qwen2.5-7b-nerd-uncensored-MFANN-slerp.Q3_K_M.gguf 3.55 GB ddd83f3c download
Qwen2.5-7b-nerd-uncensored-MFANN-slerp.Q3_K_S.gguf 3.25 GB 2007a81e download
Q2_K 1 file 2.81 GB
Qwen2.5-7b-nerd-uncensored-MFANN-slerp.Q2_K.gguf 2.81 GB 36f435bc download
Auxiliary files 2 files 6.53 KB
README.md 4.04 KB 8bab167f download
.gitattributes 2.49 KB 3b975e15 download

README current version from Hugging Face


base_model: netcat420/Qwen2.5-7b-nerd-uncensored-MFANN-slerp
language:

  • en
    library_name: transformers
    quantized_by: mradermacher
    tags:
  • mergekit
  • merge

About

static quants of https://huggingface.co/netcat420/Qwen2.5-7b-nerd-uncensored-MFANN-slerp

weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.

Usage

If you are unsure how to use GGUF files, refer to one of TheBloke's
READMEs
for
more details, including on how to concatenate multi-part files.

Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Link Type Size/GB Notes
GGUF Q2_K 3.1
GGUF Q3_K_S 3.6
GGUF Q3_K_M 3.9 lower quality
GGUF Q3_K_L 4.2
GGUF IQ4_XS 4.4
GGUF Q4_K_S 4.6 fast, recommended
GGUF Q4_K_M 4.8 fast, recommended
GGUF Q5_K_S 5.4
GGUF Q5_K_M 5.5
GGUF Q6_K 6.4 very good quality
GGUF Q8_0 8.2 fast, best quality
GGUF f16 15.3 16 bpw, overkill

Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):

image.png

And here are Artefact2's thoughts on the matter:
https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to
questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH, for letting
me use its servers and providing upgrades to my workstation to enable
this work in my free time. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.

README history 3 versions

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

  1. 2025-01-25auto-patch README.md2634b544 KB
    Loading...
  2. 2025-01-25auto-patch README.mdd2112a03 KB
    Loading...
  3. 2025-01-25uploaded from rich1ca0a439246 B
    Loading...
Catalog is the map. Apps are the tools.

Run models on your own machine, not in the cloud.

Every model page has an "Open in Abliteration" button that hands the model directly to the first-party desktop client, at the quantization your rig can actually run. No API keys, no subscription, no prompt leakage.

Open in Abliteration