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from diffusers import StableDiffusionImg2ImgPipeline
import torch
from PIL import Image
import io
from google.colab import files
import matplotlib.pyplot as plt
import time
# Load model function
def load_model():
model_id = "nitrosocke/Ghibli-Diffusion" # Correct model ID
dtype = torch.float16 if torch.cuda.is_available() else torch.float32
print("Loading model...")
pipe = StableDiffusionImg2ImgPipeline.from_pretrained(model_id, torch_dtype=dtype)
pipe.to("cuda" if torch.cuda.is_available() else "cpu")
pipe.enable_attention_slicing() # Optimize memory usage
print("Model loaded!")
return pipe
# Function to generate Ghibli-style image
def generate_ghibli_image(image, pipe, strength):
image = image.convert("RGB")
image = image.resize((512, 512)) # Ensure proper size
prompt = "Ghibli-style anime painting, soft pastel colors, highly detailed, masterpiece"
print("Generating image...")
start_time = time.time()
result = pipe(prompt=prompt, image=image, strength=strength).images[0]
print(f"Image generated in {time.time() - start_time:.2f} seconds!")
return result
# Check for GPU
gpu_info = "GPU is available!" if torch.cuda.is_available() else "Warning: GPU not available. Processing will be slow."
print(gpu_info)
# Load the model
pipe = load_model()
# Upload image section
print("Please upload your image file:")
uploaded = files.upload()
if uploaded:
file_name = list(uploaded.keys())[0]
image = Image.open(io.BytesIO(uploaded[file_name]))
# Display original image
plt.figure(figsize=(5, 5))
plt.imshow(image)
plt.noscript("Original Image")
plt.axis('off')
plt.show()
# Ask for strength input with error handling
while True:
try:
strength = float(input("Enter stylization strength (0.3-0.8, recommended 0.6): "))
strength = max(0.3, min(0.8, strength)) # Clamp between 0.3 and 0.8
break
except ValueError:
print("Invalid input. Please enter a number between 0.3 and 0.8.")
# Generate and display the result
result_img = generate_ghibli_image(image, pipe, strength)
plt.figure(figsize=(5, 5))
plt.imshow(result_img)
plt.noscript("Ghibli Portrait")
plt.axis('off')
plt.show()
# Save the output image and offer download
output_filename = f"ghibli_portrait_{file_name}"
result_img.save(output_filename)
files.download(output_filename)
print(f"Image saved as {output_filename} and download initiated!")
else:
print("No file was uploaded. Please run the cell again and upload an image.")
🚀 How to Generate Ghibli Images Using your Python Code?
🍵 Even You can make your own API
🌟 Just open below link in Chrome https://colab.research.google.com/ (They provide platform to run python code.)
❤️ Click + New Notebook (Once click open window like below).
🥷 Put Above code in “Start coding or generate with ai” & put below code.
🌭 Once you add code and click on run icon. It’s take 2 second for run
🧿 Wait untill upload your inage box appears.
💮 After Appears Choose file.
😱 Wait 1 to 2 minute. Your image ready & download automatic.
🍒 Generate Unlimited Ghibli Images for Free 🤫.
🚀 How to Generate Ghibli Images Using your Python Code?
🍵 Even You can make your own API
🌟 Just open below link in Chrome https://colab.research.google.com/ (They provide platform to run python code.)
❤️ Click + New Notebook (Once click open window like below).
🥷 Put Above code in “Start coding or generate with ai” & put below code.
🌭 Once you add code and click on run icon. It’s take 2 second for run
🧿 Wait untill upload your inage box appears.
💮 After Appears Choose file.
😱 Wait 1 to 2 minute. Your image ready & download automatic.
🍒 Generate Unlimited Ghibli Images for Free 🤫.
@CodingCoursePro
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from diffusers import StableDiffusionImg2ImgPipeline
import torch
from PIL import Image
import io
from google.colab import files
import matplotlib.pyplot as plt
import time
# Load model function
def load_model():
model_id = "nitrosocke/Ghibli-Diffusion" # Correct model ID
dtype = torch.float16 if torch.cuda.is_available() else torch.float32
print("Loading model...")
pipe = StableDiffusionImg2ImgPipeline.from_pretrained(model_id, torch_dtype=dtype)
pipe.to("cuda" if torch.cuda.is_available() else "cpu")
pipe.enable_attention_slicing() # Optimize memory usage
print("Model loaded!")
return pipe
# Function to generate Ghibli-style image
def generate_ghibli_image(image, pipe, strength):
image = image.convert("RGB")
image = image.resize((512, 512)) # Ensure proper size
prompt = "Ghibli-style anime painting, soft pastel colors, highly detailed, masterpiece"
print("Generating image...")
start_time = time.time()
result = pipe(prompt=prompt, image=image, strength=strength).images[0]
print(f"Image generated in {time.time() - start_time:.2f} seconds!")
return result
# Check for GPU
gpu_info = "GPU is available!" if torch.cuda.is_available() else "Warning: GPU not available. Processing will be slow."
print(gpu_info)
# Load the model
pipe = load_model()
# Upload image section
print("Please upload your image file:")
uploaded = files.upload()
if uploaded:
file_name = list(uploaded.keys())[0]
image = Image.open(io.BytesIO(uploaded[file_name]))
# Display original image
plt.figure(figsize=(5, 5))
plt.imshow(image)
plt.noscript("Original Image")
plt.axis('off')
plt.show()
# Ask for strength input with error handling
while True:
try:
strength = float(input("Enter stylization strength (0.3-0.8, recommended 0.6): "))
strength = max(0.3, min(0.8, strength)) # Clamp between 0.3 and 0.8
break
except ValueError:
print("Invalid input. Please enter a number between 0.3 and 0.8.")
# Generate and display the result
result_img = generate_ghibli_image(image, pipe, strength)
plt.figure(figsize=(5, 5))
plt.imshow(result_img)
plt.noscript("Ghibli Portrait")
plt.axis('off')
plt.show()
# Save the output image and offer download
output_filename = f"ghibli_portrait_{file_name}"
result_img.save(output_filename)
files.download(output_filename)
print(f"Image saved as {output_filename} and download initiated!")
else:
print("No file was uploaded. Please run the cell again and upload an image.")
🚀 How to Generate Ghibli Images Using your Python Code?
🍵 Even You can make your own API
🌟 Just open below link in Chrome https://colab.research.google.com/ (They provide platform to run python code.)
❤️ Click + New Notebook (Once click open window like below).
🥷 Put Above code in “Start coding or generate with ai” & put below code.
🌭 Once you add code and click on run icon. It’s take 2 second for run
🧿 Wait untill upload your inage box appears.
💮 After Appears Choose file.
😱 Wait 1 to 2 minute. Your image ready & download automatic.
🍒 Generate Unlimited Ghibli Images for Free 🤫.
@CodingCoursePro
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Top 5 Small AI Coding Models That You Can Run Locally
1️⃣ gpt-oss-20b
A fast, open-weight OpenAI reasoning and coding model you can run locally for IDE assistants and low-latency tools.
2️⃣ Qwen3-VL-32B-Instruct
A powerful open-source coding model that understands screenshots, UI flows, diagrams, and code together.
3️⃣ Apriel-1.5-15B-Thinker
A reasoning-first coding model that thinks step-by-step before writing reliable production-ready code.
4️⃣ Seed-OSS-36B-Instruct
A high-performance open coding model built for multi-file repositories, refactoring, and agent workflows.
5️⃣ Qwen3-30B-A3B-Instruct
An efficient MoE coding model delivering large-model reasoning power with small-model compute for local use.
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Double Tap ❤️ For More
1️⃣ gpt-oss-20b
A fast, open-weight OpenAI reasoning and coding model you can run locally for IDE assistants and low-latency tools.
2️⃣ Qwen3-VL-32B-Instruct
A powerful open-source coding model that understands screenshots, UI flows, diagrams, and code together.
3️⃣ Apriel-1.5-15B-Thinker
A reasoning-first coding model that thinks step-by-step before writing reliable production-ready code.
4️⃣ Seed-OSS-36B-Instruct
A high-performance open coding model built for multi-file repositories, refactoring, and agent workflows.
5️⃣ Qwen3-30B-A3B-Instruct
An efficient MoE coding model delivering large-model reasoning power with small-model compute for local use.
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✅ Web Development Basics You Should Know 🌐💡
Understanding the foundations of web development is the first step toward building websites and web apps.
1️⃣ What is Web Development?
Web development is the process of creating websites and web applications. It includes everything from a basic HTML page to full-stack apps.
Types of Web Dev:
- Frontend: What users see (HTML, CSS, JavaScript)
- Backend: Server-side logic, databases (Node.js, Python, etc.)
- Full Stack: Both frontend + backend
2️⃣ How the Web Works
When you visit a website:
- The browser (client) sends a request via HTTP
- The server processes it and sends back a response (HTML, data)
- Your browser renders it on the screen
Example: Typing
3️⃣ HTML (HyperText Markup Language)
Defines the structure of web pages.
*4️⃣ CSS (Cascading Style Sheets)*
Adds *style* to HTML: colors, layout, fonts.
*5️⃣ JavaScript (JS)*
Makes the website *interactive* (buttons, forms, animations).
*6️⃣ Responsive Design*
Using *media queries* to make websites mobile-friendly.
*7️⃣ DOM (Document Object Model)*
JS can interact with page content using the DOM.
*8️⃣ Git & GitHub*
Version control to track changes and collaborate.
*9️⃣ API (Application Programming Interface)*
APIs let you pull or send data between your app and a server.
🔟 Hosting Your Website
You can deploy websites using platforms like Vercel, Netlify, or GitHub Pages.
💡 Once you know these basics, you can move on to frameworks like React, backend tools like Node.js, and databases like MongoDB.
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Understanding the foundations of web development is the first step toward building websites and web apps.
1️⃣ What is Web Development?
Web development is the process of creating websites and web applications. It includes everything from a basic HTML page to full-stack apps.
Types of Web Dev:
- Frontend: What users see (HTML, CSS, JavaScript)
- Backend: Server-side logic, databases (Node.js, Python, etc.)
- Full Stack: Both frontend + backend
2️⃣ How the Web Works
When you visit a website:
- The browser (client) sends a request via HTTP
- The server processes it and sends back a response (HTML, data)
- Your browser renders it on the screen
Example: Typing
www.example.com sends a request → DNS resolves IP → Server sends back the HTML → Browser displays it 3️⃣ HTML (HyperText Markup Language)
Defines the structure of web pages.
<h1>Welcome</h1>
<p>This is my first website.</p>
*4️⃣ CSS (Cascading Style Sheets)*
Adds *style* to HTML: colors, layout, fonts.
h1 {
color: blue;
text-align: center;
}*5️⃣ JavaScript (JS)*
Makes the website *interactive* (buttons, forms, animations).
<button onclick="alert('Hello!')">Click Me</button>*6️⃣ Responsive Design*
Using *media queries* to make websites mobile-friendly.
@media (max-width: 600px) {
body {
font-size: 14px;
}
}*7️⃣ DOM (Document Object Model)*
JS can interact with page content using the DOM.
document.getElementById("demo").innerText = "Changed!";*8️⃣ Git & GitHub*
Version control to track changes and collaborate.
git init
git add .
git commit -m "First commit"
git push
*9️⃣ API (Application Programming Interface)*
APIs let you pull or send data between your app and a server.
fetch('https://api.weatherapi.com')
.then(res => res.json())
.then(data => console.log(data));🔟 Hosting Your Website
You can deploy websites using platforms like Vercel, Netlify, or GitHub Pages.
💡 Once you know these basics, you can move on to frameworks like React, backend tools like Node.js, and databases like MongoDB.
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✅ HTML Basics You Must Know 🧱🌐
HTML (HyperText Markup Language) is the foundation of every web page. It structures content like text, images, links, and forms.
1️⃣ Basic HTML Structure
Explanation:
⦁
⦁
⦁
⦁
2️⃣ Headings and Paragraphs
3️⃣ Links and Images
4️⃣ Lists
5️⃣ Tables
6️⃣ Forms
7️⃣ Div & Span
⦁
⦁
💡 Practice HTML in a live editor like CodePen or JSFiddle to see instant results!
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HTML (HyperText Markup Language) is the foundation of every web page. It structures content like text, images, links, and forms.
1️⃣ Basic HTML Structure
<!DOCTYPE html>
<html>
<head>
<noscript>My First Page</noscript>
</head>
<body>
<h1>Hello World!</h1>
<p>This is a paragraph.</p>
</body>
</html>
Explanation:
⦁
<!DOCTYPE html> → Declares HTML5⦁
<html> → Root element⦁
<head> → Info about the page (noscript, meta)⦁
<body> → Visible content2️⃣ Headings and Paragraphs
<h1>Main Heading</h1>
<h2>Subheading</h2>
<p>This is a paragraph.</p>
3️⃣ Links and Images
<a href="https://google.com">Visit Google</a>
<img src="image.jpg" alt="Image" width="200">
4️⃣ Lists
<ul>
<li>HTML</li>
<li>CSS</li>
</ul>
<ol>
<li>Step 1</li>
<li>Step 2</li>
</ol>
5️⃣ Tables
<table border="1">
<tr>
<th>Name</th>
<th>Age</th>
</tr>
<tr>
<td>Alice</td>
<td>25</td>
</tr>
</table>
6️⃣ Forms
<form>
<input type="text" placeholder="Your name">
<input type="email" placeholder="Your email">
<button type="submit">Submit</button>
</form>
7️⃣ Div & Span
⦁
<div> → Block-level container⦁
<span> → Inline container<div style="background: lightgray;">Box</div>
<span style="color: red;">Text</span>
💡 Practice HTML in a live editor like CodePen or JSFiddle to see instant results!
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OnSpace Mobile App builder: Build AI Apps in minutes
👉https://www.onspace.ai/agentic-app-builder?via=tg_abt
With OnSpace, you can build AI Mobile Apps by chatting with AI, and publish to PlayStore or AppStore.
What will you get:
- Create app by chatting with AI;
- Integrate with Any top AI power just by giving order (like Sora2, Nanobanan Pro & Gemini 3 Pro);
- Download APK,AAB file, publish to AppStore.
- Add payments and monetize like in-app-purchase and Stripe.
- Functional login & signup.
- Database + dashboard in minutes.
- Full tutorial on YouTube and within 1 day customer service
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👉https://www.onspace.ai/agentic-app-builder?via=tg_abt
With OnSpace, you can build AI Mobile Apps by chatting with AI, and publish to PlayStore or AppStore.
What will you get:
- Create app by chatting with AI;
- Integrate with Any top AI power just by giving order (like Sora2, Nanobanan Pro & Gemini 3 Pro);
- Download APK,AAB file, publish to AppStore.
- Add payments and monetize like in-app-purchase and Stripe.
- Functional login & signup.
- Database + dashboard in minutes.
- Full tutorial on YouTube and within 1 day customer service
@CodingCoursePro
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Cookies are small pieces of data stored in a user's browser, commonly used for session management, personalizing, and tracking.
In JavaScript, the document.cookie property allows you to create, read, update, and delete cookies. Here is a concise guide on managing cookies using JavaScript.
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❤2
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🎯 Build 1 Industry-Level Project
🏅 IBM Certification Included
👨🏫 Mentor-Led Classroom Learning
📍 Offline in: Noida | Bengaluru | Hyderabad | Pune | Kolkata
🧳 Perfect for Minor/Major Projects Portfolio
🔧 MERN Stack:
https://gfgcdn.com/tu/WC6/
📊 Data Science:
https://gfgcdn.com/tu/WC7/
🔥 What You’ll Build:
• MERN: Full LMS with auth, roles, payments, AWS deploy
• Data Science: End-to-end GenAI apps (chatbots, RAG, recsys)
📢 Limited Seats – Register Now!
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