Model Card for Turkish-Gemma-9b-v0.1_textholder_filtered_bsc_output_10k_1
This model is a fine-tuned version of
None
.
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="None", 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
PEFT 0.17.1
TRL: 0.23.1
Transformers: 4.57.0
Pytorch: 2.8.0
Datasets: 4.1.1
Tokenizers: 0.22.1
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 sghosts CosmosGemma-9b_bsc_filtered on huggingface.co
3
Total runs
0
24-hour runs
2
3-day runs
2
7-day runs
1
30-day runs
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