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.
- Libraries
- llama-cpp-python
How to use tda45/TdAI with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="tda45/TdAI", filename="llama.cpp/models/ggml-vocab-aquila.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- 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
| // AI Assistant Tutorial Response | |
| export const AI_TUTORIAL_MD = String.raw` | |
| # Building a Modern Chat Application with SvelteKit | |
| I'll help you create a **production-ready chat application** using SvelteKit, TypeScript, and WebSockets. This implementation includes real-time messaging, user authentication, and message persistence. | |
| ## π Quick Start | |
| First, let's set up the project: | |
| ${'```'}bash | |
| npm create svelte@latest chat-app | |
| cd chat-app | |
| npm install | |
| npm install socket.io socket.io-client | |
| npm install @prisma/client prisma | |
| npm run dev | |
| ${'```'} | |
| ## π Project Structure | |
| ${'```'} | |
| chat-app/ | |
| βββ src/ | |
| β βββ routes/ | |
| β β βββ +layout.svelte | |
| β β βββ +page.svelte | |
| β β βββ api/ | |
| β β βββ socket/+server.ts | |
| β βββ lib/ | |
| β β βββ components/ | |
| β β β βββ ChatMessage.svelte | |
| β β β βββ ChatInput.svelte | |
| β β βββ stores/ | |
| β β βββ chat.ts | |
| β βββ app.html | |
| βββ prisma/ | |
| β βββ schema.prisma | |
| βββ package.json | |
| ${'```'} | |
| ## π» Implementation | |
| ### WebSocket Server | |
| ${'```'}typescript | |
| // src/lib/server/socket.ts | |
| import { Server } from 'socket.io'; | |
| import type { ViteDevServer } from 'vite'; | |
| export function initializeSocketIO(server: ViteDevServer) { | |
| const io = new Server(server.httpServer || server, { | |
| cors: { | |
| origin: process.env.ORIGIN || 'http://localhost:5173', | |
| credentials: true | |
| } | |
| }); | |
| io.on('connection', (socket) => { | |
| console.log('User connected:', socket.id); | |
| socket.on('message', async (data) => { | |
| // Broadcast to all clients | |
| io.emit('new-message', { | |
| id: crypto.randomUUID(), | |
| userId: socket.id, | |
| content: data.content, | |
| timestamp: new Date().toISOString() | |
| }); | |
| }); | |
| socket.on('disconnect', () => { | |
| console.log('User disconnected:', socket.id); | |
| }); | |
| }); | |
| return io; | |
| } | |
| ${'```'} | |
| ### Client Store | |
| ${'```'}typescript | |
| // src/lib/stores/chat.ts | |
| import { writable } from 'svelte/store'; | |
| import io from 'socket.io-client'; | |
| export interface Message { | |
| id: string; | |
| userId: string; | |
| content: string; | |
| timestamp: string; | |
| } | |
| function createChatStore() { | |
| const { subscribe, update } = writable<Message[]>([]); | |
| let socket: ReturnType<typeof io>; | |
| return { | |
| subscribe, | |
| connect: () => { | |
| socket = io('http://localhost:5173'); | |
| socket.on('new-message', (message: Message) => { | |
| update(messages => [...messages, message]); | |
| }); | |
| }, | |
| sendMessage: (content: string) => { | |
| if (socket && content.trim()) { | |
| socket.emit('message', { content }); | |
| } | |
| } | |
| }; | |
| } | |
| export const chatStore = createChatStore(); | |
| ${'```'} | |
| ## π― Key Features | |
| β **Real-time messaging** with WebSockets | |
| β **Message persistence** using Prisma + PostgreSQL | |
| β **Type-safe** with TypeScript | |
| β **Responsive UI** for all devices | |
| β **Auto-reconnection** on connection loss | |
| ## π Performance Metrics | |
| | Metric | Value | | |
| |--------|-------| | |
| | **Message Latency** | < 50ms | | |
| | **Concurrent Users** | 10,000+ | | |
| | **Messages/Second** | 5,000+ | | |
| | **Uptime** | 99.9% | | |
| ## π§ Configuration | |
| ### Environment Variables | |
| ${'```'}env | |
| DATABASE_URL="postgresql://user:password@localhost:5432/chat" | |
| JWT_SECRET="your-secret-key" | |
| REDIS_URL="redis://localhost:6379" | |
| ${'```'} | |
| ## π’ Deployment | |
| Deploy to production using Docker: | |
| ${'```'}dockerfile | |
| FROM node:20-alpine | |
| WORKDIR /app | |
| COPY package*.json ./ | |
| RUN npm ci --only=production | |
| COPY . . | |
| RUN npm run build | |
| EXPOSE 3000 | |
| CMD ["node", "build"] | |
| ${'```'} | |
| --- | |
| *Need help? Check the [documentation](https://kit.svelte.dev) or [open an issue](https://github.com/sveltejs/kit/issues)* | |
| `; | |