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nparra10/
lora_gemma-3-4b-pt_train_img_description_256_instruction_20250915_1941

Name: lora_gemma-3-4b-pt_train_img_description_256_instruction_20250915_1941
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transformers

safetensors

generated_from_trainer

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Model Card for lora_gemma-3-4b-pt_train_img_description_256_instruction_20250915_1941

This model is a fine-tuned version of google/gemma-3-4b-pt. It has been trained using TRL.

Quick start

python

from transformers import pipeline

question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
generator = pipeline("text-generation", model="nparra10/lora_gemma-3-4b-pt_train_img_description_256_instruction_20250915_1941", 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: 0.19.1
Transformers: 4.53.2
Pytorch: 2.6.0
Datasets: 4.0.0
Tokenizers: 0.21.2

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