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Sponsored by
PoYo.AI
beomi / gemma-2-2b-it-oai-raft-sample
Model's Last Updated: November 27 2024
Introduction of gemma-2-2b-it-oai-raft-sample
Model Details of gemma-2-2b-it-oai-raft-sample
Model Card for output
This model is a fine-tuned version of unsloth/gemma-2-2b-it-bnb-4bit . It has been trained using TRL .
Quick start
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="beomi/output", 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: 0.13.0.dev0
- Transformers: 4.46.3
- Pytorch: 2.5.0
- Datasets: 3.1.0
- Tokenizers: 0.20.3
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 Gallouédec},
year = 2020,
journal = {GitHub repository},
publisher = {GitHub},
howpublished = {\url{https://github.com/huggingface/trl}}
}
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More Information About gemma-2-2b-it-oai-raft-sample huggingface.co Model
Url of gemma-2-2b-it-oai-raft-sample
gemma-2-2b-it-oai-raft-sample huggingface.co Url
Provider of gemma-2-2b-it-oai-raft-sample huggingface.co
Other API from beomi
Updated:April 03 2023
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