---
library_name: vllm
language:
- code
license: other
tags:
- code
- mistral-common
inference: false
license_name: mnpl
license_link: https://mistral.ai/licences/MNPL-0.1.md

extra_gated_description: If you want to learn more about how we process your personal data, please read our <a href="https://mistral.ai/terms/">Privacy Policy</a>.
---



# 🚀 CodingAgent-22B-v1

<p align="center">
  <img src="https://img.shields.io/badge/Model-22B-blue?style=for-the-badge">
  <img src="https://img.shields.io/badge/Architecture-Mistral-green?style=for-the-badge">
  <img src="https://img.shields.io/badge/License-Apache%202.0-orange?style=for-the-badge">
</p>

A powerful **22 Billion parameter coding language model** fine-tuned to assist with software development tasks including code generation, debugging, refactoring, documentation, reasoning, and programming assistance.

---

## ✨ Features

- 💻 High-quality code generation
- 🐞 Intelligent debugging assistance
- 🔄 Code refactoring & optimization
- 📖 Automatic documentation generation
- 🧠 Strong reasoning for complex programming tasks
- 🌐 Supports multiple programming languages
- ⚡ Optimized for Hugging Face Transformers
- 🔥 Compatible with vLLM and Text Generation Inference (TGI)

---

# 📊 Model Information

| Property | Value |
|----------|-------|
| Model Name | CodingAgent-22B-v1 |
| Base Architecture | Mistral |
| Parameters | 22 Billion |
| Framework | Transformers |
| Format | SafeTensors |
| Precision | FP16 |
| Context Length | *(Update if applicable)* |

---

# 🛠 Supported Languages

- Python
- JavaScript
- TypeScript
- Java
- C
- C++
- C#
- Go
- Rust
- PHP
- Ruby
- Kotlin
- Swift
- SQL
- HTML
- CSS
- Bash
- JSON
- YAML
- Markdown

---

# 📦 Installation

```bash
pip install transformers accelerate torch
```

---

# 🚀 Quick Start

```python
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

model_id = "kovaion/codingagent-22b-v1"

tokenizer = AutoTokenizer.from_pretrained(model_id)

model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype=torch.float16,
    device_map="auto"
)

prompt = "Write a Python function that implements binary search."

inputs = tokenizer(prompt, return_tensors="pt").to(model.device)

outputs = model.generate(
    **inputs,
    max_new_tokens=256,
    temperature=0.2
)

print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```

---

# 🎯 Ideal Use Cases

- AI Coding Assistant
- Software Development
- Code Completion
- Bug Fixing
- Code Explanation
- Competitive Programming
- Technical Interview Preparation
- Documentation Generation
- API Development
- Educational Projects

---

# ⚙️ Recommended Generation Settings

| Parameter | Value |
|-----------|-------|
| Temperature | 0.2–0.7 |
| Top-p | 0.95 |
| Max New Tokens | 512–2048 |
| Repetition Penalty | 1.05 |

---

# 📁 Repository Structure

```
config.json
generation_config.json
model-00001-of-00009.safetensors
...
model-00009-of-00009.safetensors
tokenizer.json
tokenizer.model
special_tokens_map.json
README.md
```

---

# ⚡ Performance

CodingAgent-22B-v1 is optimized for:

- Large-scale code generation
- Instruction following
- Multi-turn coding conversations
- Code reasoning
- Debugging assistance
- Algorithm implementation

---

# 🤝 Contributing

Contributions, suggestions, and feedback are always welcome.

If you discover issues or have ideas for improvements, please open an issue or submit a pull request.

---

# 📜 License

This project follows the license specified for this repository.

---

# ⭐ Support

If you find this model useful:

- ⭐ Star the repository
- ❤️ Like the model on Hugging Face
- 🔄 Share it with the community

---

# 🙏 Acknowledgements

Built using the **Mistral** architecture and the **Hugging Face Transformers** ecosystem.

Special thanks to the open-source AI community for advancing large language models.