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: 1,757 Bytes
6b9d0d8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 | <script lang="ts">
import * as Dialog from '$lib/components/ui/dialog';
import { ConversationSelection } from '$lib/components/app';
interface Props {
conversations: DatabaseConversation[];
messageCountMap?: Map<string, number>;
mode: 'export' | 'import';
onCancel: () => void;
onConfirm: (selectedConversations: DatabaseConversation[]) => void;
open?: boolean;
}
let {
conversations,
messageCountMap = new Map(),
mode,
onCancel,
onConfirm,
open = $bindable(false)
}: Props = $props();
let conversationSelectionRef: ConversationSelection | undefined = $state();
let previousOpen = $state(false);
$effect(() => {
if (open && !previousOpen && conversationSelectionRef) {
conversationSelectionRef.reset();
} else if (!open && previousOpen) {
onCancel();
}
previousOpen = open;
});
</script>
<Dialog.Root bind:open>
<Dialog.Portal>
<Dialog.Overlay class="z-[1000000]" />
<Dialog.Content class="z-[1000001] max-w-2xl">
<Dialog.Header>
<Dialog.Title>
Select Conversations to {mode === 'export' ? 'Export' : 'Import'}
</Dialog.Title>
<Dialog.Description>
{#if mode === 'export'}
Choose which conversations you want to export. Selected conversations will be downloaded
as a JSON file.
{:else}
Choose which conversations you want to import. Selected conversations will be merged
with your existing conversations.
{/if}
</Dialog.Description>
</Dialog.Header>
<ConversationSelection
bind:this={conversationSelectionRef}
{conversations}
{messageCountMap}
{mode}
{onCancel}
{onConfirm}
/>
</Dialog.Content>
</Dialog.Portal>
</Dialog.Root>
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