Vedika-Code-Pro-v1 / README.md
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---
license: mit
library_name: transformers
---
# Vedika-Code-Pro-v1
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## Introduction
**Vedika-Code-Pro-v1** is a state-of-the-art language model designed for advanced coding and reasoning tasks.
### System Prompt
The default system prompt for Vedika-Code-Pro-v1 is:
> "You are Vedika, built by Veda Labs for coding in India."
## Model Downloads
<div align="center">
| **Model** | **#Total Params** | **#Activated Params** | **Context Length** | **Precision** | **Download** |
| :---: | :---: | :---: | :---: | :---: | :---: |
| Vedika-Code-Pro-v1 | 1.6T | 49B | 1M | FP4 + FP8 Mixed* | [HuggingFace](https://huggingface.co/Veda-Labs/Vedika-Code-Pro-v1) |
</div>
*\*FP4 + FP8 Mixed: MoE expert parameters use FP4 precision; most other parameters use FP8.*
## Chat Template
This release does not include a Jinja-format chat template. Instead, we provide a dedicated `encoding` folder with Python scripts and test cases demonstrating how to encode messages in OpenAI-compatible format into input strings for the model, and how to parse the model's text output. Please refer to the [`encoding`](encoding/README.md) folder for full documentation.
A brief example:
```python
from encoding_vedika_code_pro_v1 import encode_messages, parse_message_from_completion_text
messages = [
{"role": "user", "content": "hello"},
{"role": "assistant", "content": "Hello! I am Vedika.", "reasoning_content": "thinking..."},
{"role": "user", "content": "1+1=?"}
]
# messages -> string
prompt = encode_messages(messages, thinking_mode="thinking")
# string -> tokens
import transformers
tokenizer = transformers.AutoTokenizer.from_pretrained("Veda-Labs/Vedika-Code-Pro-v1")
tokens = tokenizer.encode(prompt)
```
## How to Run Locally
Please refer to the [inference](inference/README.md) folder for detailed instructions on running Vedika-Code-Pro-v1 locally, including model weight conversion and interactive chat demos.
For local deployment, we recommend setting the sampling parameters to `temperature = 1.0, top_p = 1.0`.
## License
This repository and the model weights are licensed under the [MIT License](LICENSE).
## Citation
```
@misc{vedalabs2026vedikacodeprov1,
title={Vedika-Code-Pro-v1},
author={Veda-Labs},
year={2026},
}
```
## Contact
- **Website:** https://vedalabs.online
- **Hugging Face:** https://huggingface.co/Veda-Labs
- **GitHub:** https://github.com/vedalabs-tech
- **X (Twitter):** https://x.com/VedaLabsAI
- **Email:** vedalabs.veda@gmail.com