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mradermacher/Cyber-Ornith-1.5-9B-OBLITERATED-GGUF overview

About < quantize version: 2 < output tensor quantised: 1 < convert type: hf < vocab type: < tags: < quants: x f16 Q4 K S Q2 K Q8 0 Q6 K Q3 K M Q3 K S Q3 K L Q4…

transformersggufDuoNeuralcybersecurityagenticqloraunslothqwen3_5obliteratedterminalclireasoningfunction-callingtool-useendataset:oi-uae/cyber-securitydataset:hotdogs/uka-cyber-datasetdataset:trend-cybertron/Primus-Reasoningdataset:Lite-Coder/LiteCoder-Terminal-SFTdataset:rajistics/openhands-synthetic-conversationsdataset:emirkaanozdemr/bash_command_data_6Kdataset:NousResearch/hermes-function-calling-v1dataset:open-thoughts/OpenThoughts3-1.2Mbase_model:DuoNeural/Cyber-Ornith-1.5-9B-OBLITERATED

Runs locally from ~3.56 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Repository Files & Downloads

12 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
Cyber-Ornith-1.5-9B-OBLITERATED.IQ4_XS.ggufGGUFGGUF4.87 GBDownload
Cyber-Ornith-1.5-9B-OBLITERATED.Q2_K.ggufGGUFGGUF3.56 GBDownload
Cyber-Ornith-1.5-9B-OBLITERATED.Q3_K_L.ggufGGUFGGUF4.59 GBDownload
Cyber-Ornith-1.5-9B-OBLITERATED.Q3_K_M.ggufGGUFGGUF4.31 GBDownload
Cyber-Ornith-1.5-9B-OBLITERATED.Q3_K_S.ggufGGUFGGUF3.97 GBDownload
Cyber-Ornith-1.5-9B-OBLITERATED.Q4_K_M.ggufGGUFGGUF5.24 GBDownload
Cyber-Ornith-1.5-9B-OBLITERATED.Q4_K_S.ggufGGUFGGUF4.98 GBDownload
Cyber-Ornith-1.5-9B-OBLITERATED.Q5_K_M.ggufGGUFGGUF6.02 GBDownload
Cyber-Ornith-1.5-9B-OBLITERATED.Q5_K_S.ggufGGUFGGUF5.87 GBDownload
Cyber-Ornith-1.5-9B-OBLITERATED.Q6_K.ggufGGUFGGUF6.85 GBDownload
Cyber-Ornith-1.5-9B-OBLITERATED.Q8_0.ggufGGUFGGUF8.87 GBDownload
Cyber-Ornith-1.5-9B-OBLITERATED.f16.ggufGGUFGGUF16.69 GBDownload

Model Details

Model IDmradermacher/Cyber-Ornith-1.5-9B-OBLITERATED-GGUF
Authormradermacher
Pipeline—
Licenseapache-2.0
Base modelDuoNeural/Cyber-Ornith-1.5-9B-OBLITERATED
Last modified2026-09-25T17:18:02.000Z

Model README

---

base_model: DuoNeural/Cyber-Ornith-1.5-9B-OBLITERATED

datasets:

  • oi-uae/cyber-security
  • hotdogs/uka-cyber-dataset
  • trend-cybertron/Primus-Reasoning
  • Lite-Coder/LiteCoder-Terminal-SFT
  • rajistics/openhands-synthetic-conversations
  • emirkaanozdemr/bash_command_data_6K
  • NousResearch/hermes-function-calling-v1
  • open-thoughts/OpenThoughts3-1.2M

language:

  • en

library_name: transformers

license: apache-2.0

mradermacher:

readme_rev: 1

quantized_by: mradermacher

tags:

  • DuoNeural
  • cybersecurity
  • agentic
  • qlora
  • unsloth
  • qwen3_5
  • obliterated
  • terminal
  • cli
  • reasoning
  • function-calling
  • tool-use

---

About

<!-- ### quantize_version: 2 -->

<!-- ### output_tensor_quantised: 1 -->

<!-- ### convert_type: hf -->

<!-- ### vocab_type: -->

<!-- ### tags: -->

<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->

<!-- ### quants_skip: -->

<!-- ### skip_mmproj: -->

static quants of https://huggingface.co/DuoNeural/Cyber-Ornith-1.5-9B-OBLITERATED

<!-- provided-files -->

For a convenient overview and download list, visit our model page for this model.

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Cyber-Ornith-1.5-9B-OBLITERATED-i1-GGUF

Usage

If you are unsure how to use GGUF files, refer to one of [TheBloke's

READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) 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 | 3.9 | |

| GGUF | Q3_K_S | 4.4 | |

| GGUF | Q3_K_M | 4.7 | lower quality |

| GGUF | Q3_K_L | 5.0 | |

| GGUF | IQ4_XS | 5.3 | |

| GGUF | Q4_K_S | 5.5 | fast, recommended |

| GGUF | Q4_K_M | 5.7 | fast, recommended |

| GGUF | Q5_K_S | 6.4 | |

| GGUF | Q5_K_M | 6.6 | |

| GGUF | Q6_K | 7.5 | very good quality |

| GGUF | Q8_0 | 9.6 | fast, best quality |

| GGUF | f16 | 18.0 | 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.

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