Text Generation
Safetensors
GGUF
English
reasoning
reinforcement-learning
grpo
small-language-model
samsung-ennovatex
conversational
Instructions to use OmnipotentFool/Aurvion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use OmnipotentFool/Aurvion with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf OmnipotentFool/Aurvion:Q4_K_M # Run inference directly in the terminal: llama cli -hf OmnipotentFool/Aurvion:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf OmnipotentFool/Aurvion:Q4_K_M # Run inference directly in the terminal: llama cli -hf OmnipotentFool/Aurvion:Q4_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf OmnipotentFool/Aurvion:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf OmnipotentFool/Aurvion:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf OmnipotentFool/Aurvion:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf OmnipotentFool/Aurvion:Q4_K_M
Use Docker
docker model run hf.co/OmnipotentFool/Aurvion:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use OmnipotentFool/Aurvion with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "OmnipotentFool/Aurvion" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OmnipotentFool/Aurvion", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/OmnipotentFool/Aurvion:Q4_K_M
- Ollama
How to use OmnipotentFool/Aurvion with Ollama:
ollama run hf.co/OmnipotentFool/Aurvion:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use OmnipotentFool/Aurvion with Docker Model Runner:
docker model run hf.co/OmnipotentFool/Aurvion:Q4_K_M
- Lemonade
How to use OmnipotentFool/Aurvion with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull OmnipotentFool/Aurvion:Q4_K_M
Run and chat with the model
lemonade run user.Aurvion-Q4_K_M
List all available models
lemonade list
- Atomic Chat
File size: 1,493 Bytes
28ba115 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 | #!/usr/bin/env bash
# initialize a new worktree from a branch name:
#
# - creates a new branch from current HEAD
# - creates a new worktree in a parent folder, suffixed with the branch name
#
# sample usage:
# ./scripts/wc2wt.sh gg/new-feature-foo-bar
# ./scripts/wc2wt.sh gg/new-feature-foo-bar opencode
# ./scripts/wc2wt.sh gg/new-feature-foo-bar "cmake -B build && cmake --build build"
# ./scripts/wc2wt.sh gg/new-feature-foo-bar "bash -l"
function usage() {
echo "usage: $0 <branch_name> [cmd]"
exit 1
}
# check we are in the right directory
if [[ ! -f "scripts/wc2wt.sh" ]]; then
echo "error: this script must be run from the root of the repository"
exit 1
fi
if [[ $# -lt 1 || $# -gt 2 ]]; then
usage
fi
BRANCH=$1
if [[ -z "$BRANCH" ]]; then
echo "error: branch name must not be empty"
exit 1
fi
dir=$(basename $(pwd))
# sanitize branch name for directory name (replace / with -)
dir_suffix=$(echo "$BRANCH" | tr '/' '-')
git worktree add "../$dir-$dir_suffix" "$BRANCH" || git worktree add -b "$BRANCH" "../$dir-$dir_suffix" HEAD
og_path=$(pwd)
wt_path=$(cd "../$dir-$dir_suffix" && pwd)
echo "git worktree created in $wt_path"
cd "$wt_path"
# pi agent setup in the worktree
if [[ -f "$og_path/.pi/SYSTEM.md" && ! -f ".pi/SYSTEM.md" ]]; then
mkdir -p .pi
ln -sfn "$og_path/.pi/SYSTEM.md" .pi/SYSTEM.md
fi
if [[ $# -eq 2 ]]; then
echo "executing: $2"
eval "$2"
fi
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