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
File size: 5,196 Bytes
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import { isWebpMimeType, webpBase64UrlToPngDataURL } from './webp-to-png';
import { heicFileToJpegDataURL, isHeicMimeType } from './heic-to-jpeg';
import { FileTypeCategory } from '$lib/enums';
import { SETTINGS_KEYS } from '$lib/constants';
import { modelsStore } from '$lib/stores/models.svelte';
import { settingsStore } from '$lib/stores/settings.svelte';
import { toast } from 'svelte-sonner';
import { getFileTypeCategory } from '$lib/utils';
import { convertPDFToText } from './pdf-processing';
/**
* Read a file as a data URL (base64 encoded)
* @param file - The file to read
* @returns Promise resolving to the data URL string
*/
function readFileAsDataURL(file: File): Promise<string> {
return new Promise((resolve, reject) => {
const reader = new FileReader();
reader.onload = () => resolve(reader.result as string);
reader.onerror = () => reject(reader.error);
reader.readAsDataURL(file);
});
}
/**
* Read a file as UTF-8 text
* @param file - The file to read
* @returns Promise resolving to the text content
*/
function readFileAsUTF8(file: File): Promise<string> {
return new Promise((resolve, reject) => {
const reader = new FileReader();
reader.onload = () => resolve(reader.result as string);
reader.onerror = () => reject(reader.error);
reader.readAsText(file);
});
}
/**
* Process uploaded files into ChatUploadedFile format with previews and content
*
* This function processes various file types and generates appropriate previews:
* - Images: Base64 data URLs with format normalization (SVG/WebP → PNG)
* - Text files: UTF-8 content extraction
* - PDFs: Metadata only (processed later in conversion pipeline)
* - Audio: Base64 data URLs for preview
*
* @param files - Array of File objects to process
* @returns Promise resolving to array of ChatUploadedFile objects
*/
export async function processFilesToChatUploaded(
files: File[],
activeModelId?: string
): Promise<ChatUploadedFile[]> {
const results: ChatUploadedFile[] = [];
for (const file of files) {
const id = Date.now().toString() + Math.random().toString(36).substr(2, 9);
const base: ChatUploadedFile = {
id,
name: file.name,
size: file.size,
type: file.type,
file
};
try {
if (getFileTypeCategory(file.type) === FileTypeCategory.IMAGE) {
let preview = await readFileAsDataURL(file);
// Normalize SVG and WebP to PNG, and HEIC to compressed JPEG, in previews
if (isSvgMimeType(file.type)) {
try {
preview = await svgBase64UrlToPngDataURL(preview);
} catch (err) {
console.error('Failed to convert SVG to PNG:', err);
}
} else if (isWebpMimeType(file.type)) {
try {
preview = await webpBase64UrlToPngDataURL(preview);
} catch (err) {
console.error('Failed to convert WebP to PNG:', err);
}
} else if (isHeicMimeType(file.type)) {
try {
preview = await heicFileToJpegDataURL(file);
} catch (err) {
console.error('Failed to convert HEIC to PNG:', err);
continue;
}
}
results.push({ ...base, preview });
} else if (getFileTypeCategory(file.type) === FileTypeCategory.PDF) {
// Extract text content from PDF for preview
try {
const textContent = await convertPDFToText(file);
results.push({ ...base, textContent });
} catch (err) {
console.warn('Failed to extract text from PDF, adding without content:', err);
results.push(base);
}
// Show suggestion toast if vision model is available but PDF as image is disabled
const hasVisionSupport = activeModelId
? modelsStore.modelSupportsVision(activeModelId)
: false;
const currentConfig = settingsStore.config;
if (hasVisionSupport && !currentConfig.pdfAsImage) {
toast.info(`You can enable parsing PDF as images with vision models.`, {
duration: 8000,
action: {
label: 'Enable PDF as Images',
onClick: () => {
settingsStore.updateConfig(SETTINGS_KEYS.PDF_AS_IMAGE, true);
toast.success('PDF parsing as images enabled!', {
duration: 3000
});
}
}
});
}
} else if (getFileTypeCategory(file.type) === FileTypeCategory.AUDIO) {
// Generate preview URL for audio files
const preview = await readFileAsDataURL(file);
results.push({ ...base, preview });
} else if (getFileTypeCategory(file.type) === FileTypeCategory.VIDEO) {
// Generate preview URL for video files
const preview = await readFileAsDataURL(file);
results.push({ ...base, preview });
} else {
// Fallback: treat unknown files as text
try {
const textContent = await readFileAsUTF8(file);
results.push({ ...base, textContent });
} catch (err) {
console.warn('Failed to read file as text, adding without content:', err);
results.push(base);
}
}
} catch (error) {
console.error('Error processing file', file.name, error);
results.push(base);
}
}
return results;
}
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