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

netcat420/Qwen2.5-7B-nerd-uncensored-v0.9-MFANN-Q8_0-GGUF

netcat420 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/netcat420%2FQwen2.5-7B-nerd-uncensored-v0.9-MFANN-Q8_0-GGUF"
Response includes
  • classification m-uncensored
  • files 3
  • benchmarks 5 entries
  • hub_downloads_all_time 184
  • author_summary 60 models
  • readme_text full
10 credits · hourly refresh · ~4 KB payload Get an API key →
Abliteration classifier · v1.0.0
M-U
Primary method

Uncensored (method unknown)

No other method signals detected in this model.
Confidence
LOW
Why this label 3 signals
Weak or ambiguous signals. Best guess based on catalog patterns; treat as tentative and check the evidence below.
  • 'uncensored' in name/tags but no 'abliterated' marker
  • method not identifiable from author declaration alone
  • may be DPO fine-tune, prompt engineering, or unknown technique
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
184
39 last 30d - stable
Likes
0
Model age
21mo ago
created 2025-01-02

Training datasets

Corpora the author lists in the model card. Datasets tracked in our /datasets catalog carry a category badge linking to the workflow stage. Others open on Hugging Face.

Downloads over time
Now196→from54↑263%
07214421554 on Jan 1, 2025196 on Oct 11196 on Oct 9Jan '25Apr '25Jul '25Oct '25JanAprJulOct
Jan 1, 2025 → Oct 11 · 132 snapshots · spans 648 days

Benchmarks

Benchmark Score Source
BBH average 0.47074847580749773 OpenLLM-v2
IFEval instruct 0.6414868105515588 OpenLLM-v2
IFEval-Prompt 0.5341959334565619 OpenLLM-v2
MATH lvl 5 0.07099697885196375 OpenLLM-v2
MMLU-Pro 0.390375664893617 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

License
apache-2.0
Languages
en
Tags
transformers gguf llama-cpp gguf-my-repo en dataset:netcat420/MFANN base_model:netcat420/Qwen2.5-7B-nerd-uncensored-v0.9-MFANN base_model:quantized:netcat420/Qwen2.5-7B-nerd-uncensored-v0.9-MFANN license:apache-2.0 endpoints_compatible region:us conversational

Related

Total size
7.54 GB
Files
3
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2025-01-02 18:40

Files by quantization

Auxiliary files 3 files 7.54 GB
qwen2.5-7b-nerd-uncensored-v0.9-mfann-q8_0.gguf 7.54 GB 1675b991 download
README.md 2.03 KB 844a5f54 download
.gitattributes 1.57 KB 028c0292 download

README current version from Hugging Face


library_name: transformers
license: apache-2.0
datasets:

  • netcat420/MFANN
    language:
  • en
    base_model: netcat420/Qwen2.5-7B-nerd-uncensored-v0.9-MFANN
    tags:
  • llama-cpp
  • gguf-my-repo

netcat420/Qwen2.5-7B-nerd-uncensored-v0.9-MFANN-Q8_0-GGUF

This model was converted to GGUF format from netcat420/Qwen2.5-7B-nerd-uncensored-v0.9-MFANN using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.

Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo netcat420/Qwen2.5-7B-nerd-uncensored-v0.9-MFANN-Q8_0-GGUF --hf-file qwen2.5-7b-nerd-uncensored-v0.9-mfann-q8_0.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo netcat420/Qwen2.5-7B-nerd-uncensored-v0.9-MFANN-Q8_0-GGUF --hf-file qwen2.5-7b-nerd-uncensored-v0.9-mfann-q8_0.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.

git clone https://github.com/ggerganov/llama.cpp

Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).

cd llama.cpp && LLAMA_CURL=1 make

Step 3: Run inference through the main binary.

./llama-cli --hf-repo netcat420/Qwen2.5-7B-nerd-uncensored-v0.9-MFANN-Q8_0-GGUF --hf-file qwen2.5-7b-nerd-uncensored-v0.9-mfann-q8_0.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo netcat420/Qwen2.5-7B-nerd-uncensored-v0.9-MFANN-Q8_0-GGUF --hf-file qwen2.5-7b-nerd-uncensored-v0.9-mfann-q8_0.gguf -c 2048

README history 1 version

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

  1. 2025-01-02Upload README.md with huggingface_hube63882f2 KB
    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