Model Card for gemma-3-svg-generator

This model has been discontinued. The conclusion is that it's likely necessary to train a tokenizer for this task, which implies starting a model from scratch.

This model is a fine-tuned version of google/gemma-3-1b-it. It has been trained using TRL.

Quick start

from transformers import pipeline

question = "Generate code for a SVG (Scalable Vector Graphics) of a cat"
generator = pipeline("text-generation", model="shorecode/gemma-3-svg-generator", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=512, return_full_text=False)[0]
print(output["generated_text"])

Training procedure

This model was trained with SFT.

Framework versions

• TRL: 0.25.0
• Transformers: 4.57.1
• Pytorch: 2.8.0+cu126
• Datasets: 4.0.0
• Tokenizers: 0.22.1

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 Gallou{\'e}dec},
	year         = 2020,
	journal      = {GitHub repository},
	publisher    = {GitHub},
	howpublished = {\url{https://github.com/huggingface/trl}}
}