Safetensors
GGUF
Turkish
llama
Llama-3
instruct
finetune
chatml
gpt4
synthetic data
distillation
function calling
json mode
axolotl
roleplaying
chat
Instructions to use tda45/TdAI 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 tda45/TdAI 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 tda45/TdAI # Run inference directly in the terminal: llama cli -hf tda45/TdAI
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf tda45/TdAI # Run inference directly in the terminal: llama cli -hf tda45/TdAI
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 tda45/TdAI # Run inference directly in the terminal: ./llama-cli -hf tda45/TdAI
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 tda45/TdAI # Run inference directly in the terminal: ./build/bin/llama-cli -hf tda45/TdAI
Use Docker
docker model run hf.co/tda45/TdAI
- LM Studio
- Jan
- Ollama
How to use tda45/TdAI with Ollama:
ollama run hf.co/tda45/TdAI
- Unsloth Studio
How to use tda45/TdAI 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 tda45/TdAI 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 tda45/TdAI to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for tda45/TdAI to start chatting
- Atomic Chat new
- Docker Model Runner
How to use tda45/TdAI with Docker Model Runner:
docker model run hf.co/tda45/TdAI
- Lemonade
How to use tda45/TdAI with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tda45/TdAI
Run and chat with the model
lemonade run user.TdAI-{{QUANT_TAG}}List all available models
lemonade list
File size: 3,939 Bytes
8efb28e | 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 | import { readdirSync, readFileSync, writeFileSync, existsSync } from 'node:fs';
import { resolve } from 'path';
import type { Plugin } from 'vite';
import { TAB, NEWLINE } from '../src/lib/constants/code';
import { APPLE_DEVICES, BUILD_CONFIG, REGEX_PATTERNS, SPLASH_LINK } from '../src/lib/constants/pwa';
import type { SplashDimensions } from '../src/lib/types';
import { SplashOrientation } from '../src/lib/enums/splash.enums';
let processed = false;
const OUTPUT_DIR = process.env.LLAMA_UI_OUT_DIR ?? BUILD_CONFIG.OUTPUT_DIR;
/**
* Generate iOS splash screen <link> tags from generated apple-splash-*.png files.
* Returns an array of HTML link strings to be injected into the page head.
*/
export function generateSplashScreenLinks(outDir: string): string[] {
const files = readdirSync(outDir).filter((f) => f.match(REGEX_PATTERNS.SPLASH_FILE));
if (files.length === 0) return [];
const dimMap = new Map<string, SplashDimensions>();
for (const [dims, spec] of Object.entries(APPLE_DEVICES)) {
const [w, h] = dims.split('x').map(Number);
// logical-point dimensions
dimMap.set(`${w}x${h}`, { deviceW: spec.width, deviceH: spec.height, dpr: spec.dpr });
dimMap.set(`${h}x${w}`, { deviceW: spec.width, deviceH: spec.height, dpr: spec.dpr });
// pixel dimensions (used by actual generated splash files)
dimMap.set(`${w * spec.dpr}x${h * spec.dpr}`, {
deviceW: spec.width,
deviceH: spec.height,
dpr: spec.dpr
});
dimMap.set(`${h * spec.dpr}x${w * spec.dpr}`, {
deviceW: spec.width,
deviceH: spec.height,
dpr: spec.dpr
});
}
const lightLinks: string[] = [];
const darkLinks: string[] = [];
for (const file of files) {
const match = file.match(REGEX_PATTERNS.SPLASH_FILE);
if (!match) continue;
const orientation = match[1] as SplashOrientation;
const isDark = !!match[2];
const pixelW = parseInt(match[3]);
const pixelH = parseInt(match[4]);
const key = `${pixelW}x${pixelH}`;
const spec = dimMap.get(key);
if (!spec) {
console.warn(`Unknown splash screen dimensions: ${key} (${file})`);
continue;
}
const { deviceW, deviceH, dpr } = spec;
const media = `screen and (device-width: ${deviceW}px) and (device-height: ${deviceH}px) and (-webkit-device-pixel-ratio: ${dpr}) and (orientation: ${orientation})`;
const href = `./${file}`;
if (isDark) {
darkLinks.push(
`${SPLASH_LINK.HTML} media="${media}${SPLASH_LINK.DARK_MEDIA_SUFFIX}" href="${href}">`
);
} else {
lightLinks.push(`${SPLASH_LINK.HTML} media="${media}" href="${href}">`);
}
}
return [...lightLinks, ...darkLinks];
}
export function splashScreenPlugin(): Plugin {
return {
name: 'llamacpp:splash-screen',
apply: 'build',
closeBundle() {
setTimeout(() => {
try {
if (processed) return;
processed = true;
const outDir = resolve(OUTPUT_DIR);
const indexPath = resolve(outDir, 'index.html');
if (!existsSync(indexPath)) return;
let content = readFileSync(indexPath, 'utf-8');
// Inject iOS splash screen <link> tags into <head>.
// The @vite-pwa/assets-generator generates apple-splash-*.png files;
// this scans them and creates the <link> tags SvelteKit needs.
const splashLinks = generateSplashScreenLinks(outDir);
if (splashLinks.length > 0) {
console.log(`Generated ${splashLinks.length} apple-splash link tags`);
const splashHtml = splashLinks.map((l) => TAB + TAB + l).join(NEWLINE);
content = content.replace(
REGEX_PATTERNS.HEAD_CLOSE,
splashHtml + NEWLINE + TAB + TAB + '</head>'
);
}
// Remove trailing \r from Windows line endings
content = content.replace(/\r/g, '');
content = BUILD_CONFIG.GUIDE_COMMENT + NEWLINE + content;
writeFileSync(indexPath, content, 'utf-8');
console.log('Updated index.html');
} catch (error) {
console.error('Failed to process build output:', error);
}
}, 100);
}
};
}
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