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
- 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/forms/InputWithSuggestions.svelte from OmnipotentFool/Aurvion: direct link, hf CLI and curl.
- Browser
- Download file 1.92 kB
-
https://huggingface.co/OmnipotentFool/Aurvion/resolve/main/llama.cpp/tools/ui/src/lib/components/app/forms/InputWithSuggestions.svelte
- Command line
-
hf download hf://OmnipotentFool/Aurvion/llama.cpp/tools/ui/src/lib/components/app/forms/InputWithSuggestions.svelte
-
curl -L -o InputWithSuggestions.svelte https://huggingface.co/OmnipotentFool/Aurvion/resolve/main/llama.cpp/tools/ui/src/lib/components/app/forms/InputWithSuggestions.svelte
1.92 kB
| <script lang="ts"> | |
| import { fly } from 'svelte/transition'; | |
| import { Input } from '$lib/components/ui/input'; | |
| import { Label } from '$lib/components/ui/label'; | |
| interface Props { | |
| name: string; | |
| value: string; | |
| suggestions?: string[]; | |
| isLoadingSuggestions?: boolean; | |
| isAutocompleteActive?: boolean; | |
| autocompleteIndex?: number; | |
| onInput: (value: string) => void; | |
| onKeydown: (event: KeyboardEvent) => void; | |
| onBlur: () => void; | |
| onFocus: () => void; | |
| onSelectSuggestion: (value: string) => void; | |
| } | |
| let { | |
| name, | |
| value = '', | |
| suggestions = [], | |
| isLoadingSuggestions = false, | |
| isAutocompleteActive = false, | |
| autocompleteIndex = 0, | |
| onInput, | |
| onKeydown, | |
| onBlur, | |
| onFocus, | |
| onSelectSuggestion | |
| }: Props = $props(); | |
| </script> | |
| <div class="relative grid gap-1"> | |
| <Label for="tpl-arg-{name}" class="mb-1 text-muted-foreground"> | |
| <span> | |
| {name} | |
| <span class="text-destructive">*</span> | |
| </span> | |
| {#if isLoadingSuggestions} | |
| <span class="text-xs text-muted-foreground/50">...</span> | |
| {/if} | |
| </Label> | |
| <Input | |
| id="tpl-arg-{name}" | |
| type="text" | |
| {value} | |
| oninput={(e) => onInput(e.currentTarget.value)} | |
| onkeydown={onKeydown} | |
| onblur={onBlur} | |
| onfocus={onFocus} | |
| placeholder="Enter {name}" | |
| autocomplete="off" | |
| /> | |
| {#if isAutocompleteActive && suggestions.length > 0} | |
| <div | |
| class="absolute top-full right-0 left-0 z-10 mt-1 max-h-32 overflow-y-auto rounded-lg border border-border/50 bg-background shadow-lg" | |
| transition:fly={{ y: -5, duration: 100 }} | |
| > | |
| {#each suggestions as suggestion, i (suggestion)} | |
| <button | |
| type="button" | |
| onmousedown={() => onSelectSuggestion(suggestion)} | |
| class="w-full px-3 py-1.5 text-left text-sm hover:bg-accent {i === autocompleteIndex | |
| ? 'bg-accent' | |
| : ''}" | |
| > | |
| {suggestion} | |
| </button> | |
| {/each} | |
| </div> | |
| {/if} | |
| </div> | |