Instructions to use Aliguinga01/rule_violation2 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 Aliguinga01/rule_violation2 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 Aliguinga01/rule_violation2:F16 # Run inference directly in the terminal: llama cli -hf Aliguinga01/rule_violation2:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Aliguinga01/rule_violation2:F16 # Run inference directly in the terminal: llama cli -hf Aliguinga01/rule_violation2:F16
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 Aliguinga01/rule_violation2:F16 # Run inference directly in the terminal: ./llama-cli -hf Aliguinga01/rule_violation2:F16
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 Aliguinga01/rule_violation2:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf Aliguinga01/rule_violation2:F16
Use Docker
docker model run hf.co/Aliguinga01/rule_violation2:F16
- LM Studio
- Jan
- Ollama
How to use Aliguinga01/rule_violation2 with Ollama:
ollama run hf.co/Aliguinga01/rule_violation2:F16
- Unsloth Studio
How to use Aliguinga01/rule_violation2 with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Aliguinga01/rule_violation2 to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Aliguinga01/rule_violation2 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Aliguinga01/rule_violation2 to start chatting
- Docker Model Runner
How to use Aliguinga01/rule_violation2 with Docker Model Runner:
docker model run hf.co/Aliguinga01/rule_violation2:F16
- Lemonade
How to use Aliguinga01/rule_violation2 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Aliguinga01/rule_violation2:F16
Run and chat with the model
lemonade run user.rule_violation2-F16
List all available models
lemonade list
- Atomic Chat
File size: 4,307 Bytes
4d35814 | 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 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 | import { isSvgMimeType, svgBase64UrlToPngDataURL } from './svg-to-png';
import { isTextFileByName } from './text-files';
import { isWebpMimeType, webpBase64UrlToPngDataURL } from './webp-to-png';
import { FileTypeCategory } from '$lib/enums/files';
import { getFileTypeCategory } from '$lib/utils/file-type';
import { supportsVision } from '$lib/stores/server.svelte';
import { settingsStore } from '$lib/stores/settings.svelte';
import { toast } from 'svelte-sonner';
/**
* 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[]): 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 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);
}
}
results.push({ ...base, preview });
} else if (
getFileTypeCategory(file.type) === FileTypeCategory.TEXT ||
isTextFileByName(file.name)
) {
try {
const textContent = await readFileAsUTF8(file);
results.push({ ...base, textContent });
} catch (err) {
console.warn('Failed to read text file, adding without content:', err);
results.push(base);
}
} else if (getFileTypeCategory(file.type) === FileTypeCategory.PDF) {
// PDFs handled later when building extras; keep metadata only
results.push(base);
// Show suggestion toast if vision model is available but PDF as image is disabled
const hasVisionSupport = supportsVision();
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('pdfAsImage', 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 {
// Other files: add as-is
results.push(base);
}
} catch (error) {
console.error('Error processing file', file.name, error);
results.push(base);
}
}
return results;
}
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