PyTorch Masterclass: Part 4 – Generative Models with PyTorch
Duration: ~120 minutes
Link A: https://hackmd.io/@husseinsheikho/pytorch-4A
Link B: https://hackmd.io/@husseinsheikho/pytorch-4B
https://t.iss.one/DataScienceM🖕
Duration: ~120 minutes
Link A: https://hackmd.io/@husseinsheikho/pytorch-4A
Link B: https://hackmd.io/@husseinsheikho/pytorch-4B
#PyTorch #GenerativeAI #GANs #VAEs #DiffusionModels #Autoencoders #TextToImage #DeepLearning #MachineLearning #AI #GenerativeAdversarialNetworks #VariationalAutoencoders #StableDiffusion #DALLE #ImageGeneration #MusicGeneration #AudioSynthesis #LatentSpace #PyTorchGenerative
https://t.iss.one/DataScienceM
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🤖🧠 Diffusion Transformers with Representation Autoencoders (RAE): The Next Leap in Generative AI
🗓️ 14 Oct 2025
📚 AI News & Trends
Diffusion Transformers (DiTs) have revolutionized image and video generation enabling stunningly realistic outputs in systems like Stable Diffusion and Imagen. However, despite innovations in transformer architectures and training methods, one crucial element of the diffusion pipeline has remained largely stagnant- the autoencoder that defines the latent space. Most current diffusion models still depend on Variational ...
#DiffusionTransformers #RAE #GenerativeAI #StableDiffusion #Imagen #LatentSpace
🗓️ 14 Oct 2025
📚 AI News & Trends
Diffusion Transformers (DiTs) have revolutionized image and video generation enabling stunningly realistic outputs in systems like Stable Diffusion and Imagen. However, despite innovations in transformer architectures and training methods, one crucial element of the diffusion pipeline has remained largely stagnant- the autoencoder that defines the latent space. Most current diffusion models still depend on Variational ...
#DiffusionTransformers #RAE #GenerativeAI #StableDiffusion #Imagen #LatentSpace
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In Python, building AI-powered Telegram bots unlocks massive potential for image generation, processing, and automation—master this to create viral tools and ace full-stack interviews! 🤖
Learn more: https://hackmd.io/@husseinsheikho/building-AI-powered-Telegram-bots
https://t.iss.one/DataScienceM🦾
# Basic Bot Setup - The foundation (PTB v20+ Async)
from telegram.ext import Application, CommandHandler, MessageHandler, filters
async def start(update, context):
await update.message.reply_text(
"✨ AI Image Bot Active!\n"
"/generate - Create images from text\n"
"/enhance - Improve photo quality\n"
"/help - Full command list"
)
app = Application.builder().token("YOUR_BOT_TOKEN").build()
app.add_handler(CommandHandler("start", start))
app.run_polling()
# Image Generation - DALL-E Integration (OpenAI)
import openai
from telegram.ext import ContextTypes
openai.api_key = os.getenv("OPENAI_API_KEY")
async def generate(update: Update, context: ContextTypes.DEFAULT_TYPE):
if not context.args:
await update.message.reply_text("❌ Usage: /generate cute robot astronaut")
return
prompt = " ".join(context.args)
try:
response = openai.Image.create(
prompt=prompt,
n=1,
size="1024x1024"
)
await update.message.reply_photo(
photo=response['data'][0]['url'],
caption=f"🎨 Generated: *{prompt}*",
parse_mode="Markdown"
)
except Exception as e:
await update.message.reply_text(f"🔥 Error: {str(e)}")
app.add_handler(CommandHandler("generate", generate))
Learn more: https://hackmd.io/@husseinsheikho/building-AI-powered-Telegram-bots
#Python #TelegramBot #AI #ImageGeneration #StableDiffusion #OpenAI #MachineLearning #CodingInterview #FullStack #Chatbots #DeepLearning #ComputerVision #Programming #TechJobs #DeveloperTips #CareerGrowth #CloudComputing #Docker #APIs #Python3 #Productivity #TechTips
https://t.iss.one/DataScienceM
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