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SaketR1/uncertainty-sft
uncertainty-sft is a image-text-to-text model from SaketR1. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for transformers.
This model is a fine-tuned version of Qwen/Qwen3.5-2B. It has been trained using TRL.
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From the Hugging Face model README
This model is a fine-tuned version of Qwen/Qwen3.5-2B. It has been trained using TRL.
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="SaketR1/uncertainty-sft", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])
This model was trained with SFT.
Cite TRL as:
@software{vonwerra2020trl,
title = {{TRL: Transformers Reinforcement Learning}},
author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
license = {Apache-2.0},
url = {https://github.com/huggingface/trl},
year = {2020}
}