README.md

---
license: mit
datasets:
- Meforgers/Aixr-Thinkable-V1
language:
- tr
- en
base_model:
- meta-llama/Llama-3.1-8B
tags:
- code
- medical
- math
- turkish
- türkçe
- coding
- yazılım
- programlama
- thinkable
- düşünebilen
- düşünen
new_version: Aixr/Aixr
---
# LLama-3.1-Thinkable: Bilingual AI Expert in Mathematics and Programming

LLama-3.1-Thinkable is a fine-tuned version of LLama 3.1, specifically designed to excel in **bilingual (Turkish and English)** communication, advanced **mathematics**, and **programming** tasks. This model combines enhanced reasoning capabilities with strong multilingual proficiency, offering a cutting-edge solution for users in diverse fields.

---

## 🚀 Features

1. **Bilingual Expertise**
   - Fluent in both **Turkish** and **English**.
   - Designed to seamlessly understand and respond in either language.
   - Ideal for users who switch between these languages or require multilingual solutions.

2. **Mathematics Mastery**
   - Excels in solving advanced mathematical problems, including algebra, calculus, and statistics.
   - Provides step-by-step explanations for better understanding.

3. **Programming Proficiency**
   - Supports a wide range of programming languages, including **Python**, **JavaScript**, **C++**, and more.
   - Assists with debugging, algorithm design, and code optimization.
   - Generates clear and efficient code snippets for complex tasks.

4. **Thinkable AI: Enhanced Reasoning**
   - Fine-tuned for improved logical and critical thinking.
   - Capable of breaking down complex concepts into understandable insights.

---

## 🔧 Technical Details

- **Base Model:** LLama 3.1
- **Fine-tuning Dataset:** 
  - High-quality bilingual datasets (Turkish-English).
  - Specialized datasets for mathematics and programming tasks.
- **Parameter Count:** 5.25B & 8B
---

## 📚 Use Cases

- **Education:**
  - Learn programming and advanced mathematics with detailed explanations.
  - Solve bilingual academic tasks in Turkish and English.

- **Development:**
  - Generate production-ready code.
  - Debug complex applications and find optimized solutions.

- **AI Research:**
  - Experiment with a high-performance bilingual model in NLP tasks.

---

## 🛠️ How to Use

Here’s how you can get started with LLama-3.1-Thinkable:

### Installation
```bash
pip install transformers
from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "aixr/llama-3.1-thinkable"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# Generate a response
inputs = tokenizer("Explain recursion in programming:", return_tensors="pt")
outputs = model.generate(inputs["input_ids"], max_length=200)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```