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prithivMLmods
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Run this model inference on single tenant GPU with unmatched speed and reliability at scale.
Model Details
Model Provider
prithivMLmods
Model Tree
Jackrong/Qwopus3.5-9B-Coder
TokenRhythm/NeoHorse-1-9B
ornith-ai/Ornith-1.5-9B
Qwen/Qwen3.5-9B
Input Modalities
Output Modalities
Supported Functionality
bash
hf download TokenRhythm/NeoHorse-1-9B \--local-dir ./models/NeoHorse-1-9Bhf download Jackrong/Qwopus3.5-9B-Coder \--local-dir ./models/Qwopus3.5-9B-Coderhf download ornith-ai/Ornith-1.5-9B \--local-dir ./models/Ornith-1.5-9Bhf download Qwen/Qwen3.5-9B \--local-dir ./models/Qwen3.5-9B
bash
python omnimergekit.py \--base models/Qwen3.5-9B --task-base ./models/Qwen3.5-9B \--source models/NeoHorse-1-9B \--source models/Qwopus3.5-9B-Coder \--source models/Ornith-1.5-9B \--weights 0.55,0.30,0.15 \--method omnimerge_v2 --density 0.53 --darex-q 0.75 --seed 42 \--no-auto-mlp-skip --skip-patterns visual.,mtp. \--output prithivMLmods/Vortex-9B-CodeCore-Merge
Tools for model merging, expert pruning, differential competence-map extraction, and GGUF quantization — omnimergekit