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/tools/ui/src/lib/components/app/dialogs/DialogExportSettings.svelte from OmnipotentFool/Aurvion: direct link, hf CLI and curl.
- Browser
- Download file 2.4 kB
-
https://huggingface.co/OmnipotentFool/Aurvion/resolve/main/llama.cpp/tools/ui/src/lib/components/app/dialogs/DialogExportSettings.svelte
- Command line
-
hf download hf://OmnipotentFool/Aurvion/llama.cpp/tools/ui/src/lib/components/app/dialogs/DialogExportSettings.svelte
-
curl -L -o DialogExportSettings.svelte https://huggingface.co/OmnipotentFool/Aurvion/resolve/main/llama.cpp/tools/ui/src/lib/components/app/dialogs/DialogExportSettings.svelte
2.4 kB
| <script lang="ts"> | |
| import * as AlertDialog from '$lib/components/ui/alert-dialog'; | |
| import { Checkbox } from '$lib/components/ui/checkbox'; | |
| import Label from '$lib/components/ui/label/label.svelte'; | |
| import { Shield, ShieldOff } from '@lucide/svelte'; | |
| let { | |
| open = $bindable(), | |
| includeSensitiveData = $bindable(false), | |
| onCancel, | |
| onConfirm | |
| }: { | |
| open: boolean; | |
| includeSensitiveData: boolean; | |
| onCancel: () => void; | |
| onConfirm: () => void; | |
| } = $props(); | |
| function handleOpenChange(newOpen: boolean) { | |
| if (!newOpen) { | |
| onCancel(); | |
| } | |
| } | |
| </script> | |
| <AlertDialog.Root {open} onOpenChange={handleOpenChange}> | |
| <AlertDialog.Content> | |
| <AlertDialog.Header> | |
| <AlertDialog.Title class="flex items-center gap-2"> | |
| {#if includeSensitiveData} | |
| <ShieldOff class="h-5 w-5 text-destructive" /> | |
| {:else} | |
| <Shield class="h-5 w-5 text-destructive" /> | |
| {/if} | |
| Export Settings | |
| </AlertDialog.Title> | |
| <AlertDialog.Description> | |
| {#if includeSensitiveData} | |
| <p class="text-amber-500"> | |
| Warning: This export will include sensitive data such as API keys and MCP server custom | |
| headers (e.g., authorization tokens). Do not share this file with anyone you don't | |
| trust. | |
| </p> | |
| {:else} | |
| <p> | |
| Sensitive data (API keys, MCP server custom headers) will not be included in the export | |
| to protect your credentials. | |
| </p> | |
| {/if} | |
| </AlertDialog.Description> | |
| </AlertDialog.Header> | |
| <div class="flex items-center gap-2 py-2"> | |
| <Checkbox id="include-sensitive" bind:checked={includeSensitiveData} /> | |
| <Label | |
| for="include-sensitive" | |
| class="text-sm leading-none peer-disabled:cursor-not-allowed peer-disabled:opacity-70" | |
| > | |
| {#if includeSensitiveData} | |
| <span class="text-destructive">Include sensitive data (not recommended)</span> | |
| {:else} | |
| <span>Include sensitive data</span> | |
| {/if} | |
| </Label> | |
| </div> | |
| <AlertDialog.Footer> | |
| <AlertDialog.Cancel onclick={onCancel}>Cancel</AlertDialog.Cancel> | |
| <AlertDialog.Action | |
| onclick={onConfirm} | |
| class="bg-destructive text-white hover:bg-destructive/80" | |
| > | |
| {#if includeSensitiveData} | |
| Export Anyway | |
| {:else} | |
| Export Without Sensitive Data | |
| {/if} | |
| </AlertDialog.Action> | |
| </AlertDialog.Footer> | |
| </AlertDialog.Content> | |
| </AlertDialog.Root> | |