Ita Latn 10mb Ppt Shuff Dyck 100mb Seed10
basemodel: goldfish-models/italatn10mb libraryname: transformers modelname: ita-latn-10mb-ppt-shuff-dyck-100mbseed10 tags: generatedfromtrainer sft trl licence: license
Model source
- Kind
- text-generation
- File size
- 74.6 MB
- Base model
- goldfish-models/ita_latn_10mb
- Version
- vmodel
- Updated
- Oct 8, 2026
- Publisher
- @fpadovani
- Tasks
- Text generation
- Source
- Hugging Face
Source description
Model Card for ita-latn-10mb-ppt-shuff-dyck-100mb_seed10
This model is a fine-tuned version of goldfish-models/ita_latn_10mb. 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/ita-latn-10mb-ppt-shuff-dyck-100mb_seed10", 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
Sources
1 sourceVerified Sep 9
Model artifacts
1 artifact
Model artifacts
1 artifactcheckpoint-1000/model.safetensors
safetensors · 74.6 MB · SHA-256 041b95c38080…1c6b · Hugging Face
DownloadSource excerpts
3 excerpts
Source excerpts
3 excerpts--- base_model: goldfish-models/ita_latn_10mb library_name: transformers model_name: ita-latn-10mb-ppt-shuff-dyck-100mb_seed10 tags: - generated_from_trainer - sft - trl licence: license --- # Model Card for ita-latn-10mb-ppt-shuff-dyck-100mb_seed10 This model is a fine-tuned version of [goldfish-models/ita_latn_10mb](https://huggingface.co/goldfish-models/ita_latn_10mb). 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/ita-latn-10mb-ppt-shuff-dyck-100mb_seed10", 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/cphbsirt) 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: 19 downloads · 0 likes · Pipeline text-generation · Library transformers · Repo fpadovani/ita-latn-10mb-ppt-shuff-dyck-100mb_seed10
Source context: 242 downloads · 0 likes · Pipeline text-generation · Library transformers · Repo fpadovani/ita-latn-10mb-ppt-shuff-dyck-100mb_seed10
