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MishraNepali/Lily-Cybersecurity-7B-Uncensored-GGUF_Q5_K_M

MishraNepali 7B GGUF
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curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/MishraNepali%2FLily-Cybersecurity-7B-Uncensored-GGUF_Q5_K_M"
Response includes
  • classification m-uncensored
  • files 3
  • author_summary 1 models
  • readme_text full
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What "m-uncensored" means · taxonomy
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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
How we label → About M-U →
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 · 30-day
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Model age
today
created 2026-10-22

Metadata

Quantizations
Q4_K
Tags
llama.cpp gguf quantized cybersecurity uncensored q4_k_m q5_k_m text-generation base_model:NiroshanDb23/Lily-Cybersecurity-7B-Uncensored-GGUF base_model:quantized:NiroshanDb23/Lily-Cybersecurity-7B-Uncensored-GGUF license:apache-2.0 endpoints_compatible
Total size
4.07 GB
Files
3
Quantizations
2
Registered
2026-10-22 19:00
Last updated on HF
2026-10-22 19:07
Source huggingface.co/MishraNepali/Lily-Cybersecurity-7B-Uncensored-GGUF_Q5_K_M ↗

Files by quantization

Q4_K 1 file 4.07 GB
model-Q4_K_M.gguf 4.07 GB 1b391e08 download
Auxiliary files 2 files 2.63 KB
.gitattributes 1.54 KB c51b7dce download
README.md 1.09 KB 2fa270aa download

README current version from Hugging Face

Lily-Cybersecurity-7B-Uncensored-GGUF_Q5_K_M

Credits & License

This is a re-quantized version of an existing GGUF model. (And size of it converted from 13.5GB to 4.07GB)
So it can be used on CPU with 16GB of RAM (Also can be run on Google Colab).

Lineage:

My Contribution:

  • Re-quantized the intermediate GGUF file into Q4_K_M and Q5_K_M formats to reduce RAM usage for inference.
  • Alarm: Quantized version can hallucinate.
  • Recommended context window: 4096 tokens (or higher if hardware permits).
    License:
    This derivative work is distributed under the Apache 2.0 license, inherited from the original model.
    Please refer to the original model card for full terms and disclaimer.
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