CorelynAI/LeonCode

Corelyn Leon GGUF Model

Specifications :

• Model Name: Corelyn Leonicity Leon
• Base Name: Leon_1B
• Type: Instruct / Fine-tuned
• Architecture: Maincoder
• Size: 1B parameters
• Organization: Corelyn

Model Overview

Corelyn Leonicity Leon is a 1-billion parameter LLaMA-based instruction-tuned model, designed for general-purpose assistant tasks and knowledge extraction. It is a fine-tuned variant optimized for instruction-following use cases.

• Fine-tuning type: Instruct

• Base architecture: Maincoder

• Parameter count: 3B

This model is suitable for applications such as:

• Algorithms

• Websites

• Python, JavaScript, Java...

• Code and text generation

Usage

Download from : LeonCode_1B

# pip install pip install llama-cpp-python

from llama_cpp import Llama

# Load the model (update the path to where your .gguf file is)
llm = Llama(model_path="path/to/the/file/LeonCode_1B.gguf")

# Create chat completion
response = llm.create_chat_completion(
    messages=[{"role": "user", "content": "Create a python sorting algorithm"}]
)

# Print the generated text
print(response.choices[0].message["content"])