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
Download llama.cpp/common/console.h from OmnipotentFool/Aurvion: direct link, hf CLI and curl.
- Browser
- Download file 1.22 kB
-
https://huggingface.co/OmnipotentFool/Aurvion/resolve/main/llama.cpp/common/console.h
- Command line
-
hf download hf://OmnipotentFool/Aurvion/llama.cpp/common/console.h
-
curl -L -o console.h https://huggingface.co/OmnipotentFool/Aurvion/resolve/main/llama.cpp/common/console.h
1.22 kB
| // Console functions | |
| enum display_type { | |
| DISPLAY_TYPE_RESET = 0, | |
| DISPLAY_TYPE_INFO, | |
| DISPLAY_TYPE_PROMPT, | |
| DISPLAY_TYPE_REASONING, | |
| DISPLAY_TYPE_USER_INPUT, | |
| DISPLAY_TYPE_ERROR | |
| }; | |
| namespace console { | |
| void init(bool use_simple_io, bool use_advanced_display); | |
| void cleanup(); | |
| void set_display(display_type display); | |
| bool readline(std::string & line, bool multiline_input); | |
| using completion_callback = std::function<std::vector<std::pair<std::string, size_t>>(std::string_view, size_t)>; | |
| void set_completion_callback(completion_callback cb); | |
| namespace spinner { | |
| void start(); | |
| void stop(); | |
| } | |
| // note: the logging API below output directly to stdout | |
| // it can negatively impact performance if used on inference thread | |
| // only use in in a dedicated CLI thread | |
| // for logging in inference thread, use log.h instead | |
| LLAMA_COMMON_ATTRIBUTE_FORMAT(1, 2) | |
| void log(const char * fmt, ...); | |
| LLAMA_COMMON_ATTRIBUTE_FORMAT(1, 2) | |
| void error(const char * fmt, ...); | |
| void flush(); | |
| } | |