Arti Code Mini is a 3B-parameter coding assistant fine-tuned by Merkium AI for local deployment on consumer hardware. It targets clean, well-structured code generation and multi-turn debugging assistance without a dependency on cloud inference.

Table of Contents

Model Details
Intended Use
Installation
Usage
Hardware Requirements
Example Prompts
Limitations
Citation
License
Contact

Quick start

bash

pip install transformers torch accelerate bitsandbytes
python -c "
from transformers import pipeline
pipe = pipeline('text-generation', model='Merkiumai/Arti-code-mini', device_map='auto')
print(pipe([{'role': 'user', 'content': 'Write a function that reverses a string.'}], max_new_tokens=200)[0]['generated_text'][-1]['content'])
"

Model Details

Property	Value
Developer	Merkium AI
Parameters	3 Billion
Fine-tuning method	QLoRA (LoRA via Unsloth)
Primary use case	Coding assistant
Context length	2,048 tokens
Precision	float16 / 4-bit quantized
License	Apache 2.0
tuned	Adamas Mini 1

Intended Use

In scope:

Writing and completing code across multiple languages
Debugging and explaining existing code
Generating functions, classes, algorithms, and scripts
Learning support for programming concepts and best practices

Out of scope:

General conversation or non-coding tasks
Fully autonomous code generation without human review
Production systems without independent testing and validation

Installation

pip install transformers torch accelerate bitsandbytes

Usage

python

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model_name = "Merkiumai/Arti-code-mini"

tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
    model_name,
    torch_dtype=torch.float16,
    device_map="auto",
    trust_remote_code=True
)

messages = [
    {"role": "user", "content": "Write a Python function that checks if a number is prime."}
]

text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(text, return_tensors="pt").to(model.device)

outputs = model.generate(
    **inputs,
    max_new_tokens=300,
    temperature=0.3,
    do_sample=True,
    pad_token_id=tokenizer.eos_token_id
)

response = tokenizer.decode(outputs[0][inputs.input_ids.shape[-1]:], skip_special_tokens=True)
print(response)

Chat formatting is applied automatically via tokenizer.apply_chat_template(). The underlying format:

text

### System:
You are Arti Code Mini, a helpful coding assistant created by Merkium AI.

### User:
Write a Python function that reverses a string.

### Arti:
def reverse_string(s: str) -> str:
    return s[::-1]

Hardware Requirements

Component	Minimum	Recommended
GPU VRAM	6 GB	8 GB+
RAM	8 GB	16 GB
Storage	4 GB free	8 GB free

Example Prompts

Write a Python function that checks if a string is a palindrome.
Create a FastAPI endpoint that accepts a name and returns a greeting.
Explain how binary search works and provide an implementation.
Write a class for a bank account with deposit and withdraw methods.
Write a decorator that measures the execution time of a function.
Remove duplicates from a list while preserving order.

Limitations

May occasionally produce incorrect or incomplete code.
Performs best with clear, specific, well-structured prompts.
Not suited to tasks outside coding and software development.
Context limited to 2,048 tokens per session.
All generated code should be reviewed by a human before use in production.

Citation

bibtex

@misc{artimini2025,
  title  = {Arti Code Mini: A Lightweight Local Coding Assistant},
  author = {{Merkium AI}},
  year   = {2025},
  url    = {https://huggingface.co/Merkiumai/Arti-code-mini}
}

License

Released under the Apache 2.0 license.

Contact

Model repository: huggingface.co/Merkiumai/Arti-code-mini

_{Developed and maintained by Merkium AI}