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
| const http = require('http'); | |
| const fs = require('fs').promises; | |
| const path = require('path'); | |
| // This file is used for testing wasm build from emscripten | |
| // Example build command: | |
| // emcmake cmake -B build-wasm -DGGML_WEBGPU=ON -DLLAMA_OPENSSL=OFF | |
| // cmake --build build-wasm --target test-backend-ops -j | |
| const PORT = 8080; | |
| const STATIC_DIR = path.join(__dirname, '../build-wasm/bin'); | |
| console.log(`Serving static files from: ${STATIC_DIR}`); | |
| const mimeTypes = { | |
| '.html': 'text/html', | |
| '.js': 'text/javascript', | |
| '.css': 'text/css', | |
| '.png': 'image/png', | |
| '.jpg': 'image/jpeg', | |
| '.gif': 'image/gif', | |
| '.svg': 'image/svg+xml', | |
| '.json': 'application/json', | |
| '.woff': 'font/woff', | |
| '.woff2': 'font/woff2', | |
| }; | |
| async function generateDirListing(dirPath, reqUrl) { | |
| const files = await fs.readdir(dirPath); | |
| let html = ` | |
| <!DOCTYPE html> | |
| <html> | |
| <head> | |
| <title>Directory Listing</title> | |
| <style> | |
| body { font-family: Arial, sans-serif; padding: 20px; } | |
| ul { list-style: none; padding: 0; } | |
| li { margin: 5px 0; } | |
| a { text-decoration: none; color: #0066cc; } | |
| a:hover { text-decoration: underline; } | |
| </style> | |
| </head> | |
| <body> | |
| <h1>Directory: ${reqUrl}</h1> | |
| <ul> | |
| `; | |
| if (reqUrl !== '/') { | |
| html += `<li><a href="../">../ (Parent Directory)</a></li>`; | |
| } | |
| for (const file of files) { | |
| const filePath = path.join(dirPath, file); | |
| const stats = await fs.stat(filePath); | |
| const link = encodeURIComponent(file) + (stats.isDirectory() ? '/' : ''); | |
| html += `<li><a href="${link}">${file}${stats.isDirectory() ? '/' : ''}</a></li>`; | |
| } | |
| html += ` | |
| </ul> | |
| </body> | |
| </html> | |
| `; | |
| return html; | |
| } | |
| const server = http.createServer(async (req, res) => { | |
| try { | |
| // Set COOP and COEP headers | |
| res.setHeader('Cross-Origin-Opener-Policy', 'same-origin'); | |
| res.setHeader('Cross-Origin-Embedder-Policy', 'require-corp'); | |
| res.setHeader('Cache-Control', 'no-store, no-cache, must-revalidate, proxy-revalidate'); | |
| res.setHeader('Pragma', 'no-cache'); | |
| res.setHeader('Expires', '0'); | |
| const filePath = path.join(STATIC_DIR, decodeURIComponent(req.url)); | |
| const stats = await fs.stat(filePath); | |
| if (stats.isDirectory()) { | |
| const indexPath = path.join(filePath, 'index.html'); | |
| try { | |
| const indexData = await fs.readFile(indexPath); | |
| res.writeHeader(200, { 'Content-Type': 'text/html' }); | |
| res.end(indexData); | |
| } catch { | |
| // No index.html, generate directory listing | |
| const dirListing = await generateDirListing(filePath, req.url); | |
| res.writeHeader(200, { 'Content-Type': 'text/html' }); | |
| res.end(dirListing); | |
| } | |
| } else { | |
| const ext = path.extname(filePath).toLowerCase(); | |
| const contentType = mimeTypes[ext] || 'application/octet-stream'; | |
| const data = await fs.readFile(filePath); | |
| res.writeHeader(200, { 'Content-Type': contentType }); | |
| res.end(data); | |
| } | |
| } catch (err) { | |
| if (err.code === 'ENOENT') { | |
| res.writeHeader(404, { 'Content-Type': 'text/plain' }); | |
| res.end('404 Not Found'); | |
| } else { | |
| res.writeHeader(500, { 'Content-Type': 'text/plain' }); | |
| res.end('500 Internal Server Error'); | |
| } | |
| } | |
| }); | |
| server.listen(PORT, () => { | |
| console.log(`Server running at http://localhost:${PORT}/`); | |
| }); | |