jjzha / tiny-aya-global-german-sft-lr2e-4

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Total runs: 9
24-hour runs: 0
7-day runs: -2
30-day runs: 2
Model's Last Updated: May 26 2026
text-generation

Introduction of tiny-aya-global-german-sft-lr2e-4

Model Details of tiny-aya-global-german-sft-lr2e-4

Model Card for tiny-aya-global-german.jsonl-sft-lr2e-4

This model is a fine-tuned version of CohereLabs/tiny-aya-global . 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 0.18.1
  • TRL: 0.28.0
  • Transformers: 4.57.3
  • Pytorch: 2.9.1+rocm6.4
  • Datasets: 4.5.0
  • Tokenizers: 0.22.2
Citations

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}
}

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9
Total runs
0
24-hour runs
-2
3-day runs
-2
7-day runs
2
30-day runs

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Updated:February 09 2025