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Ba2han / TR_CPTs
Model's Last Updated: July 30 2026
text-generation
Introduction of TR_CPTs
Model Details of TR_CPTs
Model Card for TR_CPTs
This model is a fine-tuned version of Ba2han/random_model . 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="Ba2han/TR_CPTs", 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: 0.24.0
- Transformers: 5.5.0
- Pytorch: 2.11.0
- Datasets: 4.8.0
- Tokenizers: 0.22.2
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}}
}
Runs of Ba2han TR_CPTs on huggingface.co
175
Total runs
-1
24-hour runs
-6
3-day runs
-24
7-day runs
-197
30-day runs
More Information About TR_CPTs huggingface.co Model
Url of TR_CPTs
TR_CPTs huggingface.co Url
Provider of TR_CPTs huggingface.co
Other API from Ba2han
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