Update README.md

README.md

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 license: mit
 language:
 - en
+- zh
+- fr
+- es
+- pt
+- de
+- it
+- ru
+- ja
+- ko
+- vi
+- th
+- ar
+- fa
+- he
+- tr
+- cs
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+datasets:
+- openai/gsm8k
+- HuggingFaceH4/ultrachat_200k
+library_name: transformers
 ---
-![Header](./Atlas-Pro.png)
+![Header](./Atlas-Pro.png)
+# **Atlas Pro**
+
+### **Model Overview**
+**Atlas Pro** (Previously known as '🏆 Atlas-Experiment 0403 🧪' in AtlasUI) is an advanced language model (LLM) built on top of **Atlas Flash**. It's designed to provide exceptional performance for professional tasks like coding, mathematics, and scientific problem-solving. Atlas Pro builds on Atlas Flash by adding more fine-tuning and specialization, making it perfect for researchers and advanced users.
+
+---
+
+### **Key Features**
+- **Improved Problem-Solving:** Handles tricky tasks in programming, math, and sciences better than most models.
+- **Advanced Code Generation:** Produces clean and efficient code, but may still miss edge cases occasionally.
+- **Domain Expertise:** Focused on technical and scientific domains but works well in general contexts too.
+- **Reasoning Improvement:** In this version of Atlas, I have enhanced it's reasoning via synthetic data from models such as Gemini-2.0 Flash Thinking so that it can improve on reasoning.
+---
+
+### **Intended Use Cases**
+Atlas Pro works best for:
+- **Technical Professionals:** Helping developers, engineers, and scientists solve complex problems.
+- **Educational Assistance:** Offering clear, step-by-step help for students and teachers.
+- **Research Support:** Assisting in theoretical and applied science work.
+- **Enterprise Tools:** Integrating into company workflows for smarter systems.
+
+---
+
+### **NOTICE**
+Atlas Pro is built on **Atlas Flash** and improved to meet high standards. Here’s how it’s made:
+
+1. **Base Model:** Built upon **Atlas Flash**, which is already quite capable.
+2. **Fine-Tuning Details:**
+   - Used datasets specific to programming, math, and scientific challenges and overall reasoning abilities.
+   - Refined its performance for professional scenarios.
+3. **Performance Highlights:**
+   - Beats benchmarks with high accuracy, though occasional tweaks might still improve outputs.
+---
+
+### **Limitations**
+- **Knowledge Cutoff:** It doesn’t know about anything recent unless updated.
+- **Hardware Requirements:** Needs high-end GPUs to run smoothly.
+- **Specialization Bias:** While amazing in its focus areas, general chat capabilities might not be as good as other models.
+- **Token Leakage:** In some very rare cases (~1/167), Atlas Pro will experience some token leakage.
+
+---
+
+### **Licensing**
+Atlas Pro is released under the **MIT**, which prohibits harmful uses. Make sure to follow the rules in the license agreement.
+
+---
+
+### **Acknowledgments**
+Created by **Spestly** as part of the **Astral Model Family**, Atlas Pro builds on the strong foundation of **Atlas Flash**. Special thanks to **Deepseek's R1 Qwen Distilles** for helping make it happen.
+
+---
+
+### **Usage**
+You can use Atlas Pro with this code snippet:
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load the Atlas Pro model
+model_name = "Spestly/Atlas-R1-Pro-1.5B-Preview"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Generate a response
+prompt = "Write a Python function to calculate the Fibonacci sequence."
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_length=200)
+response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+print(response)
+```