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Brunobkr/OFFFELLIA_Q2_K_huihui-ai_MTP-hybrid-Qwen3.8-27B-abliterated.gguf overview

<p align="center" <img src="capa.png" alt="ΩFFΣLLIα llama.cpp Helicoidal Quantization" width="100%" style="border radius: 12px; box shadow: 0 10px 30px rgba 16…

ggufllama.cppquantizationofferliahelicoidal-sieveggmlcplusplustext-generationptenlicense:mitendpoints_compatibleregion:usconversational

Runs locally from ~10.12 GB disk (12 GB VRAM class GPUs with llama.cpp / guIDE).

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text-generation
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1 GGUF files detected
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OFFFELLIA_Q2_K_huihui-ai_MTP-hybrid-Qwen3.8-27B-abliterated.ggufGGUFQ2_K_HUIHUI10.12 GBDownload

Model Details

Model IDBrunobkr/OFFFELLIA_Q2_K_huihui-ai_MTP-hybrid-Qwen3.8-27B-abliterated.gguf
AuthorBrunobkr
Pipelinetext-generation
Licensemit
Base model
Last modified2026-08-16T20:11:42.000Z

Model README

---

license: mit

language:

  • pt
  • en

library_name: gguf

pipeline_tag: text-generation

tags:

  • llama.cpp
  • gguf
  • quantization
  • offerlia
  • helicoidal-sieve
  • ggml
  • cplusplus

pretty_name: ΩFFΣLLIα — llama.cpp Helicoidal Quantization

---

<p align="center">

<img src="capa.png" alt="ΩFFΣLLIα llama.cpp Helicoidal Quantization" width="100%" style="border-radius: 12px; box-shadow: 0 10px 30px rgba(168, 85, 247, 0.2);" />

</p>

<h1 align="center">ΩFFΣLLIα — llama.cpp Helicoidal Quantization </h1>

<p align="center">

<strong>Fork de alta performance do llama.cpp ZETAHELICOIDAL ( quants.py )</strong>

</p>

<p align="center">

<a href="#-visão-geral"><img src="https://img.shields.io/badge/GGUF-v3%20Native-purple?style=for-the-badge" alt="GGUF Native"></a>

<a href="#-tabela-de-arquivos-modificados"><img src="https://img.shields.io/badge/GGML-Quant%20Q4__2__H-fuchsia?style=for-the-badge" alt="Quant Q4_2_H"></a>

<a href="#-como-compilar-e-usar"><img src="https://img.shields.io/badge/C%2B%2B-17%20Build-blueviolet?style=for-the-badge" alt="C++ Build"></a>

<a href="https://huggingface.co"><img src="https://img.shields.io/badge/Hugging%20Face-Compatible-orange?style=for-the-badge" alt="HuggingFace Ready"></a>

</p>

---

📌 Visão Geral

O ΩFFΣLLIα é um fork otimizado do ecossistema llama.cpp / GGML, projetado para integrar avanços da Teoria Aritmético-Harmônica de Becker ao pipeline de inferência de Modelos de Linguagem de Grande Porte (LLMs).

---

🚀 Como Compilar e Usar

1. Compilar o llama.cpp Otimizado

cd llama.cpp
mkdir -p build && cd build
cmake .. -DLLAMA_BUILD_EXAMPLES=ON
cmake --build . --config Release -j$(nproc)

2. Converter Modelo Hugging Face para GGUF Q4_2_H

python3 llama.cpp/convert_hf_to_gguf.py path/to/hf-model \
  --outtype q4_2_h \
  --outfile models/modelo-q4_2_h.gguf

3. Quantizar Modelo F16/F32 Existente

./llama.cpp/build/bin/llama-quantize ./models/modelo-f16.gguf ./models/modelo-q4_2_h.gguf Q4_2_H

4. Executar Inferência via CLI

./llama.cpp/build/bin/llama-cli -m ./models/modelo-q4_2_h.gguf -p "ΩFFΣLLIα: Explique a Teoria Helicoidal" -n 256

5. Executar a Aplicação Web & Dashboard

npm run build
npm start

---

<p align="center">

Desenvolvido para alta eficiência em execução local e integração com o ecossistema Hugging Face.

</p>

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