imatrix
Qwen3.8-27B-iMatrix-NVFP4-MTP-GGUFQwen3.5-9B-The-Defiant-Fable-Uncensored-Heretic-NEO-IMATRIX-MAX-MTP-GGUFQwen3.6-40B-Claude-4.6-Opus-Deckard-Heretic-Uncensored-Thinking-NEO-CODE-Di-IMatrix-MAX-GGUFQwen3.6-27B-Heretic-Uncensored-FINETUNE-NEO-CODE-Di-IMatrix-MAX-GGUFQwen3.8-27B-Uncensored-Cyber-agentic-imatrix-GGUFQwen3.8-Flash-Next-ROCmFP4-FAST-imatrix-GGUFOpenAi-GPT-oss-20b-abliterated-uncensored-NEO-Imatrix-ggufOpenAi-GPT-oss-20b-HERETIC-uncensored-NEO-Imatrix-gguf
Datasets
All datasets matching “imatrix”imatrix-calibration
Importance Matrix Calibration Datasets
This repository provides calibration datasets used to generate importance matrices (imatrix), which are required to minimize errors when quantizing models with LLaMA C++.
The llama-imatrix program cannot handle parquet files directly and thus requires them to be converted into text format first. There are many ways to do this but a simple approach is to use DuckDB with the following command: duckdb -noheader -ascii -c "SELECT content FROM… See the full description on the dataset page: https://huggingface.co/datasets/eaddario/imatrix-calibration.imatrix-storageimatriximatrix
Input files for generating the Importance Matrix
Which file to use for generating the importance matrix
Not all importance matrices are equal. The best results are obtained when using a source file similar to the
training data. Size also matters: the bigger the model (eg: 70b vs 13b) and the higher the quant (eg: q6k_ vs iq3_xs),
the bigger the source file needs to be to make an impact. Multiple input files can be combined if needed;
for example:
cat multilingual.txt… See the full description on the dataset page: https://huggingface.co/datasets/froggeric/imatrix.QwQ-32B-abliterated-131k-GGUF-Yarn-Imatrix
QwQ-32B-Abliterated-131k-GGUF-Yarn-Imatrix
High-Fidelity Semantic Simulation & Orchestration AI Model
Will this pass the random stupid benchmarks that exist today? I don't know, nor care. I don't need my local AI model to know some random city capital of a foreign country. I need a local AI model that can simulate with high semantic fidelity. Why? Because your AI may be able to spit random facts. I want an AI that knows when to Google facts. I want an AI that tracks hundreds of… See the full description on the dataset page: https://huggingface.co/datasets/magiccodingman/QwQ-32B-abliterated-131k-GGUF-Yarn-Imatrix.bartowski-imatrix-v5-semantic
Bartowski iMatrix Calibration v5 (Semantic Chunking)
A processed version of bartowski's v5 imatrix calibration data using semantic boundary detection optimized for the v5 data structure.
Dataset Summary
Metric
Value
Total samples
2,075
Chunking method
V5-optimized semantic boundary detection
Chunk size
200+ characters (no upper limit, preserves document integrity)
Languages
English, German, Spanish, French, Italian, Swedish, Russian, Arabic, Chinese… See the full description on the dataset page: https://huggingface.co/datasets/lemon07r/bartowski-imatrix-v5-semantic.
ik_llama_imatrix_converterWebGPU-reka-flash-3-21b-reasoning-uncensored-max-neo-imatrix-ggufWebGPU-qwen3-jan-v1-4b-grand-horror-day1-to-day7-evolved-imatrix-ggufqwen3-6-40b-claude-4-6-opus-deckard-heretic-uncensored-thinking-neo-code-di-imatrix-maWebGPU-qwen3-6-27b-heretic-uncensored-finetune-neo-code-di-imatrix-max-ggufWebGPU-glm-4-7-flash-uncensored-heretic-neo-code-imatrix-max-gguf