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
Aurvion / llama.cpp /tools /ui /src /lib /components /app /chat /ChatScreen /ChatScreenProcessingInfo.svelte
Download llama.cpp/tools/ui/src/lib/components/app/chat/ChatScreen/ChatScreenProcessingInfo.svelte from OmnipotentFool/Aurvion: direct link, hf CLI and curl.
- Browser
- Download file 3.77 kB
-
https://huggingface.co/OmnipotentFool/Aurvion/resolve/main/llama.cpp/tools/ui/src/lib/components/app/chat/ChatScreen/ChatScreenProcessingInfo.svelte
- Command line
-
hf download hf://OmnipotentFool/Aurvion/llama.cpp/tools/ui/src/lib/components/app/chat/ChatScreen/ChatScreenProcessingInfo.svelte
-
curl -L -o ChatScreenProcessingInfo.svelte https://huggingface.co/OmnipotentFool/Aurvion/resolve/main/llama.cpp/tools/ui/src/lib/components/app/chat/ChatScreen/ChatScreenProcessingInfo.svelte
3.77 kB
| <script lang="ts"> | |
| import { untrack } from 'svelte'; | |
| import { PROCESSING_INFO_TIMEOUT } from '$lib/constants'; | |
| import { useProcessingState } from '$lib/hooks/use-processing-state.svelte'; | |
| import { chatStore, isLoading, isChatStreaming } from '$lib/stores/chat.svelte'; | |
| import { activeMessages, activeConversation } from '$lib/stores/conversations.svelte'; | |
| import { config } from '$lib/stores/settings.svelte'; | |
| import { getProcessingInfoContext } from '$lib/contexts'; | |
| import { page } from '$app/state'; | |
| const processingState = useProcessingState(); | |
| const processingInfoCtx = getProcessingInfoContext(); | |
| let showProcessingInfo = $derived(processingInfoCtx.showProcessingInfo); | |
| let isCurrentConversationLoading = $derived(isLoading()); | |
| let isStreaming = $derived(isChatStreaming()); | |
| let processingDetails = $derived(processingState.getTechnicalDetails()); | |
| let processingVisible = $derived(processingDetails.length > 0); | |
| let { onVisibilityChange }: { onVisibilityChange?: (visible: boolean) => void } = $props(); | |
| $effect(() => { | |
| onVisibilityChange?.(processingVisible); | |
| }); | |
| $effect(() => { | |
| const conversation = activeConversation(); | |
| untrack(() => chatStore.setActiveProcessingConversation(conversation?.id ?? null)); | |
| }); | |
| $effect(() => { | |
| const keepStatsVisible = config().keepStatsVisible; | |
| const shouldMonitor = keepStatsVisible || isCurrentConversationLoading || isStreaming; | |
| if (shouldMonitor) { | |
| processingState.startMonitoring(); | |
| } | |
| if (!isCurrentConversationLoading && !isStreaming && !keepStatsVisible) { | |
| const timeout = setTimeout(() => { | |
| if (!config().keepStatsVisible && !isChatStreaming()) { | |
| processingState.stopMonitoring(); | |
| } | |
| }, PROCESSING_INFO_TIMEOUT); | |
| return () => clearTimeout(timeout); | |
| } | |
| }); | |
| $effect(() => { | |
| const conversation = activeConversation(); | |
| const messages = activeMessages() as DatabaseMessage[]; | |
| const keepStatsVisible = config().keepStatsVisible; | |
| if (keepStatsVisible && conversation) { | |
| if (messages.length === 0) { | |
| untrack(() => chatStore.clearProcessingState(conversation.id)); | |
| return; | |
| } | |
| if (!isCurrentConversationLoading && !isStreaming) { | |
| untrack(() => chatStore.restoreProcessingStateFromMessages(messages, conversation.id)); | |
| } | |
| } | |
| }); | |
| </script> | |
| <div | |
| class={[ | |
| 'chat-processing-info-container pointer-events-none relative', | |
| page.params.id && showProcessingInfo && 'visible' | |
| ]} | |
| > | |
| <div class="chat-processing-info-content absolute bottom-4 left-1/2 -translate-x-1/2"> | |
| {#each processingDetails as detail (detail)} | |
| <span class="chat-processing-info-detail pointer-events-auto backdrop-blur-sm">{detail}</span> | |
| {/each} | |
| </div> | |
| </div> | |
| <style> | |
| .chat-processing-info-container { | |
| position: sticky; | |
| top: 0; | |
| z-index: 10; | |
| padding: 0 1rem 0.75rem; | |
| opacity: 0; | |
| transform: translateY(50%); | |
| transition: | |
| opacity 300ms ease-out, | |
| transform 300ms ease-out; | |
| } | |
| .chat-processing-info-container.visible { | |
| opacity: 1; | |
| transform: translateY(0); | |
| } | |
| .chat-processing-info-content { | |
| display: flex; | |
| flex-wrap: wrap; | |
| align-items: center; | |
| gap: 1rem; | |
| justify-content: center; | |
| max-width: 48rem; | |
| margin: 0 auto; | |
| } | |
| .chat-processing-info-detail { | |
| color: var(--muted-foreground); | |
| font-size: 0.75rem; | |
| padding: 0.25rem 0.75rem; | |
| border-radius: 0.375rem; | |
| font-family: | |
| ui-monospace, SFMono-Regular, 'SF Mono', Consolas, 'Liberation Mono', Menlo, monospace; | |
| white-space: nowrap; | |
| } | |
| @media (max-width: 768px) { | |
| .chat-processing-info-content { | |
| gap: 0.5rem; | |
| } | |
| .chat-processing-info-detail { | |
| font-size: 0.7rem; | |
| padding: 0.2rem 0.5rem; | |
| } | |
| } | |
| </style> | |