2 2 weeks ago

Generates excellent search queries, title summaries, etc. Substantial track record. IQ2_XXS - Adequate for the strengths of this AI LLM model. Compatible with ~16GB VRAM.

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Built with Llama

Llama 3.3 is licensed under the Llama 3.3 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved.

Licensed by NVIDIA Corporation under the NVIDIA Open Model License

NOTICE

Design

Generates excellent search queries, title summaries, etc.

Substantial track record.

IQ2_XXS - Adequate for the strengths of this AI LLM model. Compatible with ~16GB VRAM.

Usage

ollama_pull_virtuoso() {
ollama pull mirage335/"$1"
ollama cp mirage335/"$1" "$1"
ollama rm mirage335/"$1"
}

ollama_pull_virtuoso Llama-3_3-Valkyrie-49B-v1-virtuoso

Recommended environment variables. KV_CACHE quantization “q4_0” in particular RECOMMENDED, unless “q8_0” is needed (eg. by Qwen-2_5-VL-7B-Instruct-virtuoso, etc).

export OLLAMA_NUM_THREADS=18
export OLLAMA_FLASH_ATTENTION=1
export OLLAMA_KV_CACHE_TYPE="q4_0"
export OLLAMA_NEW_ENGINE=true
export OLLAMA_NOHISTORY=true
export OLLAMA_NUM_PARALLEL=1
export OLLAMA_MAX_LOADED_MODELS=1

Adjust OLLAMA_NUM_THREADS and/or disable HyperThreading, etc, to prevent crippling performance loss.

CAUTION - Preservation

Pulling the model this way relies on the ollama repository, and more generally, reliability of internet services, which has been rather significantly fragile.

If possible, you should use the “Llama-3-virtuoso” project, which automatically caches an automatically installable backup copy.

https://github.com/mirage335-colossus/Llama-3-virtuoso