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Dwrko-M1.0

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rajatsainisim commited on Jun 23

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2fe12d9

1 Parent(s): 74855c7

📚 Add comprehensive usage guides and examples

- Added usage_examples.py with API integration methods
- Added HOW_TO_USE.md complete guide for all user types
- Includes examples for developers, businesses, students
- API integration, mobile apps, chatbots, and more
- Social media templates for sharing
- Ready for public use and adoption

Files changed (2) hide show

HOW_TO_USE.md +287 -0
usage_examples.py +75 -0

HOW_TO_USE.md ADDED Viewed

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+# 🚀 How to Use Dwrko-M1.0 - Complete Guide
+**Your Claude-like AI Assistant is LIVE!** Here's how you and others can use it:
+## 🌍 **For End Users (No Coding Required)**
+### **Method 1: Direct Web Access**
+```
+🔗 https://huggingface.co/spaces/dwrkotech/Dwrko-M1.0
+```
+**Steps:**
+1. Click the link above
+2. Go to "Model Setup" tab
+3. Click "Load Dwrko-M1.0 Base Model" ✅
+4. Use "Dataset Preparation" to train with your data
+5. Use "Fine-tuning" to create your specialized model
+### **What Users Can Do:**
+- 💻 **Code Generation**: "Write a Python function for sorting"
+- 🧠 **Problem Solving**: "Solve this math equation: 2x + 5 = 13"
+- 📚 **Learning**: "Explain machine learning in simple terms"
+- 🔧 **Debugging**: "Fix this Python code: [paste code]"
+## 👨‍💻 **For Developers (API Integration)**
+### **Method 1: HuggingFace Spaces API**
+```python
+import requests
+def ask_dwrko(question):
+    api_url = "https://dwrkotech-dwrko-m1-0.hf.space/api/predict"
+    payload = {
+        "data": [question],
+        "fn_index": 0  # Function index for the interface
+    }
+    response = requests.post(api_url, json=payload)
+    return response.json()["data"][0]
+# Example usage
+answer = ask_dwrko("Write a Python function to check prime numbers")
+print(answer)
+```
+### **Method 2: Gradio Client**
+```python
+from gradio_client import Client
+client = Client("https://dwrkotech-dwrko-m1-0.hf.space/")
+# Use Dwrko-M1.0
+result = client.predict(
+    "Write a function to reverse a string",
+    api_name="/predict"
+)
+print(result)
+```
+### **Method 3: Embed in Your Website**
+```html
+<!DOCTYPE html>
+<html>
+<head>
+    <title>My AI Assistant</title>
+</head>
+<body>
+    <h1>Powered by Dwrko-M1.0</h1>
+    <iframe
+        src="https://dwrkotech-dwrko-m1-0.hf.space"
+        width="100%"
+        height="600px">
+    </iframe>
+</body>
+</html>
+```
+## 🏢 **For Businesses (Custom Integration)**
+### **Method 1: Custom Chatbot**
+```python
+import gradio as gr
+import requests
+def dwrko_chatbot(message, history):
+    # Call Dwrko-M1.0 API
+    api_url = "https://dwrkotech-dwrko-m1-0.hf.space/api/predict"
+    response = requests.post(api_url, json={
+        "data": [message]
+    })
+    ai_response = response.json()["data"][0]
+    history.append([message, ai_response])
+    return history, ""
+# Create business chatbot
+with gr.Blocks(title="Company AI Assistant") as demo:
+    gr.Markdown("# 🤖 Our AI Assistant (Powered by Dwrko-M1.0)")
+    chatbot = gr.Chatbot()
+    msg = gr.Textbox(placeholder="Ask me anything about coding...")
+    msg.submit(dwrko_chatbot, [msg, chatbot], [chatbot, msg])
+demo.launch()
+```
+### **Method 2: Slack/Discord Bot**
+```python
+import discord
+import requests
+class DwrkoBot(discord.Client):
+    async def on_message(self, message):
+        if message.author == self.user:
+            return
+        if message.content.startswith('!dwrko'):
+            question = message.content[7:]  # Remove '!dwrko '
+            # Call Dwrko-M1.0
+            api_url = "https://dwrkotech-dwrko-m1-0.hf.space/api/predict"
+            response = requests.post(api_url, json={"data": [question]})
+            answer = response.json()["data"][0]
+            await message.channel.send(f"🤖 **Dwrko-M1.0**: {answer}")
+# Run bot
+bot = DwrkoBot()
+bot.run('YOUR_DISCORD_TOKEN')
+```
+## 📱 **For Mobile Apps**
+### **React Native Example**
+```javascript
+const askDwrko = async (question) => {
+  const response = await fetch('https://dwrkotech-dwrko-m1-0.hf.space/api/predict', {
+    method: 'POST',
+    headers: {
+      'Content-Type': 'application/json',
+    },
+    body: JSON.stringify({
+      data: [question]
+    })
+  });
+  const result = await response.json();
+  return result.data[0];
+};
+// Usage in React Native component
+const handleAsk = async () => {
+  const answer = await askDwrko("Explain React hooks");
+  setResponse(answer);
+};
+```
+## 🎓 **For Students & Educators**
+### **Study Assistant**
+```python
+def create_study_assistant():
+    import gradio as gr
+    def dwrko_tutor(subject, question):
+        prompt = f"As a {subject} tutor, {question}"
+        # Call Dwrko-M1.0
+        api_url = "https://dwrkotech-dwrko-m1-0.hf.space/api/predict"
+        response = requests.post(api_url, json={"data": [prompt]})
+        return response.json()["data"][0]
+    interface = gr.Interface(
+        fn=dwrko_tutor,
+        inputs=[
+            gr.Dropdown(["Python", "JavaScript", "Math", "Science"], label="Subject"),
+            gr.Textbox(label="Your Question")
+        ],
+        outputs="text",
+        title="📚 Study Assistant (Powered by Dwrko-M1.0)"
+    )
+    return interface
+# Launch study assistant
+study_app = create_study_assistant()
+study_app.launch()
+```
+## 🔥 **Advanced Use Cases**
+### **1. Code Review Assistant**
+```python
+def code_reviewer(code):
+    prompt = f"Review this code and suggest improvements:\n\n{code}"
+    # Call Dwrko-M1.0 API
+    return dwrko_response
+```
+### **2. Documentation Generator**
+```python
+def doc_generator(function_code):
+    prompt = f"Generate documentation for this function:\n\n{function_code}"
+    # Call Dwrko-M1.0 API
+    return dwrko_response
+```
+### **3. Learning Path Creator**
+```python
+def learning_path(topic, level):
+    prompt = f"Create a {level} learning path for {topic}"
+    # Call Dwrko-M1.0 API
+    return dwrko_response
+```
+## 📊 **Usage Analytics**
+### **Track Usage (Optional)**
+```python
+import datetime
+def track_usage(user_question, ai_response):
+    usage_data = {
+        "timestamp": datetime.now(),
+        "question": user_question,
+        "response": ai_response,
+        "model": "Dwrko-M1.0"
+    }
+    # Save to database or analytics service
+    save_to_analytics(usage_data)
+```
+## 🌟 **Share Your Dwrko-M1.0**
+### **Social Media Templates:**
+**Twitter:**
+```
+🤖 Just launched my own Claude-like AI assistant!
+✨ Dwrko-M1.0 specializes in:
+• Code generation & debugging
+• Mathematical reasoning
+• Problem solving
+• Educational content
+Try it FREE: https://huggingface.co/spaces/dwrkotech/Dwrko-M1.0
+#AI #MachineLearning #Coding #OpenSource
+```
+**LinkedIn:**
+```
+Excited to share my latest AI project! 🚀
+I've created Dwrko-M1.0, a specialized AI assistant for coding and reasoning tasks. Built on StarCoder2-3B and optimized for practical use.
+Key features:
+✅ Code generation across 80+ languages
+✅ Mathematical problem solving
+✅ Memory efficient (16GB RAM)
+✅ Free to use for everyone
+Check it out: https://huggingface.co/spaces/dwrkotech/Dwrko-M1.0
+#ArtificialIntelligence #SoftwareDevelopment #Innovation
+```
+## 🎯 **Next Steps for Growth**
+1. **Collect User Feedback** - Monitor usage and improve
+2. **Add More Features** - Voice input, image processing
+3. **Create Mobile App** - Native iOS/Android apps
+4. **Build Community** - Discord server, GitHub discussions
+5. **Monetization** - Premium features, API subscriptions
+---
+**🎉 Congratulations! Your Dwrko-M1.0 is now ready for the world!**
+**Users can start using it immediately at:** https://huggingface.co/spaces/dwrkotech/Dwrko-M1.0

usage_examples.py ADDED Viewed

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+#!/usr/bin/env python3
+"""
+Dwrko-M1.0 Usage Examples
+How others can use your Claude-like AI assistant
+"""
+import requests
+import json
+# Method 1: Using HuggingFace Spaces API
+def use_dwrko_via_api(prompt):
+    """Use Dwrko-M1.0 via HuggingFace Spaces API"""
+    api_url = "https://dwrkotech-dwrko-m1-0.hf.space/api/predict"
+    payload = {
+        "data": [prompt]
+    }
+    response = requests.post(api_url, json=payload)
+    return response.json()
+# Method 2: Direct Integration
+def use_dwrko_direct():
+    """Direct integration example"""
+    from transformers import AutoTokenizer, AutoModelForCausalLM
+    # Load your trained Dwrko-M1.0
+    tokenizer = AutoTokenizer.from_pretrained("dwrkotech/Dwrko-M1.0")
+    model = AutoModelForCausalLM.from_pretrained("dwrkotech/Dwrko-M1.0")
+    # Generate response
+    prompt = "Write a Python function to calculate factorial"
+    inputs = tokenizer(prompt, return_tensors="pt")
+    outputs = model.generate(**inputs, max_length=200)
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return response
+# Method 3: Gradio Interface Integration
+def create_custom_interface():
+    """Create custom interface using Dwrko-M1.0"""
+    import gradio as gr
+    def dwrko_chat(message):
+        # Call your Dwrko-M1.0 API
+        response = use_dwrko_via_api(message)
+        return response
+    # Create custom interface
+    interface = gr.Interface(
+        fn=dwrko_chat,
+        inputs="text",
+        outputs="text",
+        title="My Custom Dwrko-M1.0 Assistant",
+        description="Powered by Dwrko-M1.0"
+    )
+    return interface
+# Example usage
+if __name__ == "__main__":
+    # Test API method
+    result = use_dwrko_via_api("Explain what is machine learning")
+    print("API Response:", result)
+    # Test direct method (requires model download)
+    # result = use_dwrko_direct()
+    # print("Direct Response:", result)
+    # Launch custom interface
+    # interface = create_custom_interface()
+    # interface.launch()