Corelyn NeoH GGUF Model

Specifications :

• Model Name: Corelyn NeoH
• Base Name: NeoH-3.2
• Type: Instruct / Fine-tuned
• Architecture: LLaMA
• Size: 3B parameters
• Organization: Corelyn

Model Overview

Corelyn NeoH is a 3-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: LLaMA

• Parameter count: 3B

• Context length: 131,072 tokens

This model is suitable for applications such as:

• Chatbots and conversational AI

• Knowledge retrieval and Q&A

• Code and text generation

• Instruction-following tasks

Usage

Download from : NeoH3.2

# 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/NeoH3.2.gguf")

# Create chat completion
response = llm.create_chat_completion(
    messages=[{"role": "user", "content": "Create a Haiku about AI"}]
)

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