---

license: apache-2.0

base_model: mistralai/Ministral-3b-instruct

tags:

• ministral
• ministral3
• gguf
• text-generation
• code

pipeline_tag: text-generation

library_name: transformers

language:

• en

datasets:

• greghavens/fable-5-coding-and-debugging-traces

---

Koa-AI Code 3B (Debug GGUF)

Koa-AI-Code-3B-GGUF is a fine-tuned 3B parameter language model built on the Ministral 3B architecture. It is optimized for lightweight text generation, instruction following, and coding tasks.

---

Model Details

• Developed by: vamazing
• Model Type: Causal Language Model / Conditional Generation
• Architecture: Ministral 3 (3B parameters)
• Language(s): English
• License: Apache 2.0
• Finetuned from: mistralai/Ministral-3b-instruct

---

Quickstart & Usage

1. Running with transformers (Python)

To run the model using Hugging Face transformers (v5.5.0 or compatible):

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM

model_id = "vamazing/Koa-AI-Code-3B-GGUF"

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

prompt = "Write a Python function to check if a number is prime."
messages = [{"role": "user", "content": prompt}]
formatted_prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)

inputs = tokenizer(formatted_prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=256, do_sample=True, temperature=0.7)

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