metadata
base_model: google/gemma-3-1b-it
pipeline_tag: text-generation
library_name: transformers
model_name: gemma-3-svg-generator
tags:
- generated_from_trainer
- trl
- sft
license: gemma
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Model Card for gemma-3-svg-generator
This model is under development, results may not be good
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}}
}