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: 1,430 Bytes
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"name": "@neoconfetti/react",
"version": "1.0.0",
"description": "Confetti explosion in React 🎉🎊",
"author": "Puru Vijay",
"license": "MIT",
"bugs": {
"url": "https://github.com/puruvj/neoconfetti/issues"
},
"homepage": "https://github.com/puruvj/neoconfetti/tree/main/packages/react#readme",
"repository": {
"type": "git",
"url": "git+https://github.com/puruvj/neoconfetti.git"
},
"keywords": [
"confetti",
"party",
"fun",
"badass",
"badassery",
"svelte",
"sveltekit",
"small",
"tiny",
"performant",
"react",
"nextjs",
"remix"
],
"main": "./dist/index.js",
"module": "./dist/index.js",
"type": "module",
"types": "./dist/index.d.ts",
"files": [
"dist/*"
],
"sideEffects": false,
"exports": {
".": {
"types": "./dist/index.d.ts",
"import": {
"production": "./dist/min/index.js",
"development": "./dist/index.js"
},
"default": "./dist/min/index.js"
},
"./package.json": "./package.json"
},
"devDependencies": {
"@neoconfetti/core": "2.2.1"
},
"scripts": {
"compile:watch": "tsup --watch",
"compile": "tsup",
"size": "echo 'React size:' && brotli-size dist/min/index.js",
"pub": "pnpm compile && pnpm publish --no-git-checks --access public",
"pub:dry": "pnpm compile && pnpm publish --dry-run --no-git-checks --access public"
}
} |