README.md

---
base_model: meta-llama/Llama-3.2-1B-Instruct
library_name: transformers
model_name: Fine_tuned_html_code_generation
tags:
- generated_from_trainer
- trl
- sft
licence: license
---

# Model Card for Fine_tuned_html_code_generation

This model is a fine-tuned version of [meta-llama/Llama-3.2-1B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).

## Quick start

```python
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:
    
```bibtex
@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}}
}
```