Model Card for Model ID

~100M parameter model trained with first 1M rows of wikipedia dataset.The model is based on HF transformers.

epochs:3

Trained on RTX 5060ti 16GB VRAM 16 GB RAM

import torch
import argparse
from transformers import pipeline

def main():
    parser = argparse.ArgumentParser(description="Minimal Llama Inference")
    # This is the "model_id argument" you asked for
    parser.add_argument(
        "model_id", 
        nargs="?", 
        default="uisikdag/umitllama-small-english",
        help="Hugging Face model ID or local path"
    )
    args = parser.parse_args()

    print(f"Loading model from HF: {args.model_id}")

    # Create pipeline
    generator = pipeline(
        "text-generation",
        model=args.model_id,
        torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,
        device_map="auto",
        trust_remote_code=True
    )

    # Generate
    prompt = "The economy is:"
    print(f"\nPrompt: {prompt}")

    output = generator(
        prompt, 
        max_new_tokens=50, 
        do_sample=True, 
        temperature=0.7,
        pad_token_id=generator.tokenizer.eos_token_id
    )

    print(f"\nResponse:\n{output[0]['generated_text']}")

if __name__ == "__main__":
    main()