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payelb/PM_deberta-v3-base-ultrafeedback-rm-round2
PM_deberta-v3-base-ultrafeedback-rm-round2 is a text classification model from payelb. Use it when you need a label for a piece of text. It is set up for transformers.
This model is a fine-tuned version of payelb/PMdeberta-v3-base-ultrafeedback-rm. It has been trained using TRL.
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.safetensors738 MB · 99%
From the Hugging Face model README
This model is a fine-tuned version of payelb/PM_deberta-v3-base-ultrafeedback-rm. It has been trained using TRL.
from transformers import pipeline
text = "The capital of France is Paris."
rewarder = pipeline(model="payelb/PM_deberta-v3-base-ultrafeedback-rm-round2", device="cuda")
output = rewarder(text)[0]
print(output["score"])
This model was trained with Reward.
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}
}