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
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -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
- Llama new
- 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
Download llama.cpp/.github/workflows/server-sanitize.yml from OmnipotentFool/Aurvion: direct link, hf CLI and curl.
- Browser
- Download file 3.39 kB
-
https://huggingface.co/OmnipotentFool/Aurvion/resolve/main/llama.cpp/.github/workflows/server-sanitize.yml
- Command line
-
hf download hf://OmnipotentFool/Aurvion/llama.cpp/.github/workflows/server-sanitize.yml
-
curl -L -o server-sanitize.yml https://huggingface.co/OmnipotentFool/Aurvion/resolve/main/llama.cpp/.github/workflows/server-sanitize.yml
3.39 kB
| name: Server (sanitize) | |
| on: | |
| workflow_dispatch: # allows manual triggering | |
| inputs: | |
| sha: | |
| description: 'Commit SHA1 to build' | |
| required: false | |
| type: string | |
| slow_tests: | |
| description: 'Run slow tests' | |
| required: true | |
| type: boolean | |
| push: | |
| branches: | |
| - master | |
| paths: [ | |
| '.github/workflows/server-sanitize.yml', | |
| '**/CMakeLists.txt', | |
| '**/Makefile', | |
| '**/*.h', | |
| '**/*.hpp', | |
| '**/*.c', | |
| '**/*.cpp', | |
| 'tools/server/**.*' | |
| ] | |
| env: | |
| LLAMA_ARG_LOG_COLORS: 1 | |
| LLAMA_ARG_LOG_PREFIX: 1 | |
| LLAMA_ARG_LOG_TIMESTAMPS: 1 | |
| LLAMA_ARG_LOG_VERBOSITY: 10 | |
| concurrency: | |
| group: ${{ github.workflow }}-${{ github.ref }}-${{ github.head_ref || github.run_id }} | |
| cancel-in-progress: true | |
| jobs: | |
| server: | |
| runs-on: [self-hosted, CPU, Linux, llama-server] | |
| strategy: | |
| matrix: | |
| sanitizer: [ADDRESS, UNDEFINED] # THREAD is very slow | |
| build_type: [RelWithDebInfo] | |
| fail-fast: false | |
| steps: | |
| #- name: Dependencies | |
| # id: depends | |
| # run: | | |
| # sudo apt-get update | |
| # sudo apt-get -y install \ | |
| # build-essential \ | |
| # xxd \ | |
| # git \ | |
| # cmake \ | |
| # curl \ | |
| # wget \ | |
| # language-pack-en \ | |
| # libssl-dev | |
| - name: Clone | |
| id: checkout | |
| uses: actions/checkout@v6 | |
| with: | |
| fetch-depth: 0 | |
| ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }} | |
| - name: Setup Node.js | |
| uses: actions/setup-node@v6 | |
| with: | |
| node-version: "24" | |
| cache: "npm" | |
| cache-dependency-path: "tools/ui/package-lock.json" | |
| - name: Build | |
| id: cmake_build | |
| run: | | |
| cmake -B build \ | |
| -DLLAMA_BUILD_BORINGSSL=ON \ | |
| -DGGML_SCHED_NO_REALLOC=ON \ | |
| -DGGML_SANITIZE_ADDRESS=${{ matrix.sanitizer == 'ADDRESS' }} \ | |
| -DGGML_SANITIZE_THREAD=${{ matrix.sanitizer == 'THREAD' }} \ | |
| -DGGML_SANITIZE_UNDEFINED=${{ matrix.sanitizer == 'UNDEFINED' }} \ | |
| -DLLAMA_SANITIZE_ADDRESS=${{ matrix.sanitizer == 'ADDRESS' }} \ | |
| -DLLAMA_SANITIZE_THREAD=${{ matrix.sanitizer == 'THREAD' }} \ | |
| -DLLAMA_SANITIZE_UNDEFINED=${{ matrix.sanitizer == 'UNDEFINED' }} | |
| cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target llama-server | |
| - name: Python setup | |
| id: setup_python | |
| uses: actions/setup-python@v6 | |
| with: | |
| python-version: '3.11' | |
| pip-install: -r tools/server/tests/requirements.txt | |
| - name: Tests | |
| id: server_integration_tests | |
| if: ${{ (!matrix.disabled_on_pr || !github.event.pull_request) }} | |
| run: | | |
| cd tools/server/tests | |
| export ${{ matrix.extra_args }} | |
| pytest -v -x -m "not slow" | |
| - name: Slow tests | |
| id: server_integration_tests_slow | |
| if: ${{ (github.event.schedule || github.event.inputs.slow_tests == 'true') && matrix.build_type == 'Release' }} | |
| run: | | |
| cd tools/server/tests | |
| export ${{ matrix.extra_args }} | |
| SLOW_TESTS=1 pytest -v -x | |