Update README.md

README.md

@@ -4,12 +4,10 @@ language:
 license: mit
 tags:
 - text-generation
-- mistral
 - business
 - technology
 - assistant
 - conversational
-- safetensors
 - AI
 - problem-solving
 pipeline_tag: text-generation
@@ -18,114 +16,25 @@ widget:
 - text: How can I improve my business strategy?
 ---
 
-# SireIQ - Professional AI Assistant
+# SireIQ
 
-<div style="text-align: center;">
-  <img src="https://huggingface.co/tarvico/sireiq/resolve/main/assets/sireiq-logo.png" alt="SireIQ Logo" style="width: 200px; margin-bottom: 20px;">
-</div>
+SireIQ is an AI-powered professional assistant developed to support business, technology, productivity, and problem-solving workflows.
 
-## 🌟 About SireIQ
+It provides intelligent recommendations, explains complex concepts, assists with strategic planning, and helps users make informed decisions across a wide range of professional use cases.
 
-SireIQ is a professional AI assistant designed specifically for business, technology, and problem-solving tasks. Built on Mistral-7B-Instruct-v0.3 and fine-tuned on over 25,000 high-quality instruction samples, SireIQ provides clear, accurate, and actionable advice tailored for professionals and teams.
+The assistant generates recommendations only and should not replace professional judgment or human decision-making.
 
-## ✨ Key Features
+## Overview
 
-- **Business Strategy**: Help with go-to-market strategies, business planning, and decision-making
-- **Technology Guidance**: Explain complex technical concepts, coding assistance, and architecture recommendations
-- **Problem-Solving**: Step-by-step solutions for professional challenges
-- **Conversational**: Natural, professional dialogue with proper system prompt support
-- **Lightweight**: 7B parameters, optimized for fast inference
+- Business strategy assistance
+- Technology guidance
+- Professional problem-solving
+- Knowledge assistance
+- Conversational AI support
+- Designed for productivity and decision support
 
-## 🚀 Quick Start
+## Documentation
 
-### Using Transformers
+This public repository intentionally excludes implementation details, training methodology, and underlying model information.
 
-```python
-from transformers import AutoModelForCausalLM, AutoTokenizer
-import torch
-
-# Load model and tokenizer
-model_name = "tarvico/sireiq"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(
-    model_name,
-    torch_dtype=torch.float16,
-    device_map="auto"
-)
-
-# Define system prompt and user query
-system_prompt = "You are SireIQ, a professional AI assistant for business, technology, and problem-solving. You provide clear, accurate, and actionable advice tailored for professionals and teams."
-user_query = "What are the key steps to build a go-to-market strategy for a SaaS product?"
-
-# Format the conversation
-messages = [
-    {"role": "system", "content": system_prompt},
-    {"role": "user", "content": user_query}
-]
-inputs = tokenizer.apply_chat_template(messages, return_tensors="pt").to(model.device)
-
-# Generate response
-outputs = model.generate(
-    inputs,
-    max_new_tokens=512,
-    temperature=0.7,
-    top_p=0.9,
-    do_sample=True,
-    pad_token_id=tokenizer.eos_token_id
-)
-
-# Print the result
-response = tokenizer.decode(outputs[0], skip_special_tokens=True)
-print(response)
-```
-
-### Simple Inference
-
-```python
-from transformers import AutoModelForCausalLM, AutoTokenizer
-import torch
-
-tokenizer = AutoTokenizer.from_pretrained("tarvico/sireiq")
-model = AutoModelForCausalLM.from_pretrained(
-    "tarvico/sireiq",
-    torch_dtype=torch.float16,
-    device_map="auto"
-)
-
-prompt = "Explain AI in simple terms."
-input_ids = tokenizer(prompt, return_tensors="pt").input_ids
-output_ids = model.generate(input_ids, max_new_tokens=200)
-print(tokenizer.decode(output_ids[0], skip_special_tokens=True))
-```
-
-## 📋 Model Details
-
-| Attribute | Value |
-|-----------|-------|
-| **Base Model** |  |
-| **Parameters** | 7B |
-| **Fine-tuning Method** | LoRA |
-| **Training Samples** | 25,000+ |
-| **License** | MIT |
-| **Language** | English |
-
-## 📊 Training Data
-
-SireIQ was fine-tuned on a diverse dataset including:
-- Databricks Dolly-15k
-- OpenHermes-2.5 (business/tech filtered)
-- WizardLM Evol-Instruct-70k
-- Alpaca-cleaned
-- GSM8K (math reasoning)
-
-## 🔒 License
-
-This model is released under the MIT License. See the [LICENSE](LICENSE) file for more details.
-
-## 📞 Support
-
-For questions or issues, please open a discussion on the [Hugging Face repo](https://huggingface.co/tarvico/sireiq/discussions).
-
-## 🤝 Contributing
-
-Contributions to improve SireIQ are welcome! Please feel free to submit issues or pull requests.
+Technical documentation, model architecture, and internal development resources are maintained separately in private documentation.