v2.0: Update README.md

README.md

@@ -1,138 +1,35 @@
 ---
-title: Architech - AI Model Architect
+title: Architech — CognoSphere Model Factory
 emoji: 🏗️
 colorFrom: blue
 colorTo: purple
 sdk: gradio
-sdk_version: 6.4.0
+sdk_version: 5.23.0
 app_file: app.py
-pinned: false
-license: mit
+pinned: true
+license: apache-2.0
+short_description: Build, train, and deploy CSUMLM-class language models
 ---
 
-# 🏗️ Architech - Your Personal AI Model Architect
+# 🏗️ Architech — CognoSphere Model Factory
 
-**Create custom AI models without the headache!** Just describe what you want, and Architech handles the rest.
+> Build, train, and deploy CSUMLM-class language models
 
-## ✨ Features
+**By [Or4cl3 AI Solutions](https://github.com/or4cl3-ai-1)**
 
-### 📊 Synthetic Data Generation
-- Generate high-quality training data from simple descriptions
-- Support for multiple domains: Technology, Healthcare, Finance, Education
-- Multiple format types: Conversational, Instruction-following
-- 50-500 examples per dataset
+## Features
 
-### 🚀 Model Training
-- Fine-tune state-of-the-art models (GPT-2, DialoGPT)
-- Automatic optimization and parameter tuning
-- Direct deployment to HuggingFace Hub
-- GPU-accelerated training with efficient memory usage
+- 📊 **Synthetic Data Generation** — Domain-specific training data
+- 🚀 **Model Training** — Fine-tune with LoRA on modern base models (Gemma 4, Llama 3, TinyLlama, etc.)
+- 🧪 **Model Testing** — Interactive inference and evaluation
+- 💾 **Model Management** — Upload, download, organize models
+- 📄 **Documentation** — Auto-generated model cards and research papers
+- 💬 **Repository Chat** — Manage HuggingFace repos conversationally
 
-### 🧪 Model Testing
-- Load and test your trained models instantly
-- Interactive inference with adjustable parameters
-- Real-time generation with temperature and length controls
+## Part of the CognoSphere CSUMLM Ecosystem
 
-### 🔒 Security & Limits
-- **Rate Limiting**: Fair usage for all users
-  - Dataset Generation: 10/hour
-  - Model Training: 3/hour
-  - Model Inference: 50/hour
-- **Token Authentication**: Secure HuggingFace integration
-- **Error Handling**: Comprehensive error messages and recovery
+Architech is the model factory for the **CognoSphere Unified Multimodal Language Model (CSUMLM)** — a unified AI system integrating the CognoSphere Multimodal AI Engine (CSMAE) and CognoSphere Large Language Model (CSLLM).
 
-## 🚀 Quick Start
+## License
 
-### 1. Generate Training Data
-1. Go to the **"Generate Dataset"** tab
-2. Describe your task (e.g., "Customer support chatbot for tech products")
-3. Select domain and size
-4. Click **"Generate Dataset"**
-
-### 2. Train Your Model
-1. Go to the **"Train Model"** tab
-2. Enter your model name and HuggingFace token
-3. Choose to use synthetic data or provide your own
-4. Click **"Train Model"**
-5. Wait for training to complete (5-15 minutes)
-
-### 3. Test Your Model
-1. Go to the **"Test Model"** tab
-2. Enter your model name and token
-3. Click **"Load Model"**
-4. Enter a test prompt and generate!
-
-## 📋 Requirements
-
-- HuggingFace account with **write** token
-- For training: GPU recommended (CPU works but slower)
-- Patience during training (coffee break recommended ☕)
-
-## 🎯 Use Cases
-
-- **Customer Support Bots**: Train chatbots for specific products/services
-- **Content Generation**: Create domain-specific text generators
-- **Educational Tools**: Build tutoring and explanation systems
-- **Creative Writing**: Fine-tune for specific writing styles
-- **Technical Documentation**: Generate code explanations and docs
-
-## ⚙️ Technical Details
-
-### Supported Base Models
-- `distilgpt2` (fastest, smallest)
-- `gpt2` (balanced)
-- `microsoft/DialoGPT-small` (conversational)
-
-### Training Features
-- Gradient accumulation for memory efficiency
-- Mixed precision training (FP16)
-- Automatic learning rate optimization
-- Smart tokenization and padding
-
-### Synthetic Data Quality
-- Domain-specific vocabulary
-- Natural language variations
-- Contextually relevant examples
-- Edge case handling
-
-## 🛠️ Troubleshooting
-
-### "GPU Memory Overflow"
-- Reduce batch size to 1
-- Use smaller base model (distilgpt2)
-- Reduce dataset size
-
-### "Permission Denied"
-- Check your HuggingFace token has **WRITE** access
-- Generate new token at: https://huggingface.co/settings/tokens
-
-### "Rate Limit Exceeded"
-- Wait for the cooldown period
-- Check remaining requests in error message
-
-## 📚 Best Practices
-
-1. **Start Small**: Begin with 100 examples and 3 epochs
-2. **Be Specific**: Detailed task descriptions yield better results
-3. **Test First**: Use the Test tab before deploying
-4. **Iterate**: Train multiple versions with different parameters
-5. **Monitor**: Watch training logs for issues
-
-## 🤝 Contributing
-
-Found a bug? Have a feature request? Open an issue!
-
-## 📜 License
-
-MIT License - feel free to use and modify!
-
-## 🙏 Acknowledgments
-
-Built with:
-- [Gradio](https://gradio.app/) - Interface
-- [Transformers](https://huggingface.co/transformers/) - Models
-- [HuggingFace](https://huggingface.co/) - Infrastructure
-
----
-
-*No PhD required. Just ideas.* ✨
+Apache 2.0