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URL: https://huggingface.co/gustavobueno/falcon-h1-05b-it-ptbr

⇱ gustavobueno/falcon-h1-05b-it-ptbr · Hugging Face


Model Card for falcon-h1-05b-it-ptbr

This model is a fine-tuned version of tiiuae/Falcon-H1-0.5B-Base on the recogna-nlp/UltrachatBR dataset. 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="gustavobueno/falcon-h1-05b-it-ptbr", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])

Training procedure

👁 Visualize in Weights & Biases

This model was trained with SFT.

Framework versions

  • TRL: 0.25.0
  • Transformers: 4.57.1
  • Pytorch: 2.4.0a0+07cecf4168.nv24.5
  • Datasets: 4.4.1
  • 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}}
}
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