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Eng Latn 100mb After Ppt Dp 100mb Ckpt500 Seed455

basemodel: fpadovani/eng-latn-100mb-ppt-Dp-100mbseed455 libraryname: transformers modelname: eng-latn-100mb-after-ppt-Dp-100mb-ckpt500seed455 tags: generatedfromtrainer sft trl licence: license

Typetext-generationModèle de basefpadovani/eng-latn-100mb-ppt-Dp-100mb_seed455VersionBClasse

Source du modèle

Type
text-generation
Taille du fichier
238 MB
Modèle de base
fpadovani/eng-latn-100mb-ppt-Dp-100mb_seed455
Version
vmodel
Mis à jour
22 sept. 2026
Tâches
Génération de texte
Source
Hugging Face

Description de la source

Model Card for eng-latn-100mb-after-ppt-Dp-100mb-ckpt500_seed455

This model is a fine-tuned version of fpadovani/eng-latn-100mb-ppt-Dp-100mb_seed455. 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="fpadovani/eng-latn-100mb-after-ppt-Dp-100mb-ckpt500_seed455", 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: 0.23.0
  • Transformers: 4.56.2
  • Pytorch: 2.11.0
  • Datasets: 4.8.4
  • 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}}
}

Sources

1 source
Hugging FacePrincipalVersion 328a216c64b94439478411e951b7af39737c8e8a
huggingface.co/fpadovani/eng-latn-100mb-after-ppt-Dp-100mb-ckpt500_seed455/tree/328a216c64b94439478411e951b7af39737c8e8a

Vérifié 19 sept.

Artefacts du modèle

1 artefact

checkpoint-12000/model.safetensors

safetensors · 238 MB · SHA-256 03d53c282e8d…3d11 · Hugging Face

Download file

Extraits de sources

3 extraits

--- base_model: fpadovani/eng-latn-100mb-ppt-Dp-100mb_seed455 library_name: transformers model_name: eng-latn-100mb-after-ppt-Dp-100mb-ckpt500_seed455 tags: - generated_from_trainer - sft - trl licence: license --- # Model Card for eng-latn-100mb-after-ppt-Dp-100mb-ckpt500_seed455 This model is a fine-tuned version of [fpadovani/eng-latn-100mb-ppt-Dp-100mb_seed455](https://huggingface.co/fpadovani/eng-latn-100mb-ppt-Dp-100mb_seed455). It has been trained using [TRL](https://github.com/huggingface/trl). ## Quick start ```python 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="fpadovani/eng-latn-100mb-after-ppt-Dp-100mb-ckpt500_seed455", device="cuda") output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0] print(output["generated_text"]) ``` ## Training procedure [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/f-padovani-university-of-groningen/new_tokenizers/runs/8uj3f2mh) This model was trained with SFT. ### Framework versions - TRL: 0.23.0 - Transformers: 4.56.2 - Pytorch: 2.11.0 - Datasets: 4.8.4 - Tokenizers: 0.22.1 ## Citations Cite TRL as: ```bibtex @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}} } ```

Source context: 56 downloads · 0 likes · Pipeline text-generation · Library transformers · Repo fpadovani/eng-latn-100mb-after-ppt-Dp-100mb-ckpt500_seed455

Source context: 784 downloads · 0 likes · Pipeline text-generation · Library transformers · Repo fpadovani/eng-latn-100mb-after-ppt-Dp-100mb-ckpt500_seed455