Model Card for Fine_tuned_html_code_generation

This model is a fine-tuned version of meta-llama/Llama-3.2-1B-Instruct. It has been trained using TRL.

Quick start

from transformers import pipeline

question = "Create an HTML page that includes a navigation bar with links to \
         'Home', 'About', 'Services', and 'Contact'. Below the navigation bar,\
         add a hero section with a welcoming message and a call-to-action button\
         labeled 'Learn More'. Ensure the page is structured with a header, \
         main content area, and footer. The footer should contain copyright \
         information and social media links."
generator = pipeline("text-generation", model="Georgios-Ak/Fine_tuned_html_code_generation", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])

Training procedure

This model was trained with SFT.

Framework versions

• TRL: 0.13.0
• Transformers: 4.48.0
• Pytorch: 2.5.1+cu118
• Datasets: 2.21.0
• Tokenizers: 0.21.0

Citations

Cite TRL as:

@misc{vonwerra2022trl,
    title        = {{TRL: Transformer Reinforcement Learning}},
    author       = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
    year         = 2020,
    journal      = {GitHub repository},
    publisher    = {GitHub},
    howpublished = {\url{https://github.com/huggingface/trl}}
}