fpadovani/tur-latn-10mb-after-ppt-shuff-dyck-100mb-ckpt500_seed10 · Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Fuente del modelo
- Tipo
- Other
- Tamaño del archivo
- 74,6 MB
- Actualizado
- 26 sept 2026
- Publicador
- @fpadovani
- Fuente
- Hugging Face
Extracto de la fuente
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Fuentes
1 fuente
Fuentes
1 fuenteVerificado 7 ago
Artefactos del modelo
34 artefactos
Artefactos del modelo
34 artefactoscheckpoint-100030/model.safetensors
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Extractos de fuentes
3 extractos
Extractos de fuentes
3 extractos--- base_model: fpadovani/tur-latn-10mb-ppt-shuff-dyck-100mb_seed10 library_name: transformers model_name: tur-latn-10mb-after-ppt-shuff-dyck-100mb-ckpt500_seed10 tags: - generated_from_trainer - sft - trl licence: license --- # Model Card for tur-latn-10mb-after-ppt-shuff-dyck-100mb-ckpt500_seed10 This model is a fine-tuned version of [fpadovani/tur-latn-10mb-ppt-shuff-dyck-100mb_seed10](https://huggingface.co/fpadovani/tur-latn-10mb-ppt-shuff-dyck-100mb_seed10). 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/tur-latn-10mb-after-ppt-shuff-dyck-100mb-ckpt500_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/mnk5e1oq) 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: 925 downloads · 0 likes · Pipeline text-generation · Library transformers · Repo fpadovani/tur-latn-10mb-after-ppt-shuff-dyck-100mb-ckpt500_seed10
Source context: 880 downloads · 0 likes · Pipeline text-generation · Library transformers · Repo fpadovani/tur-latn-10mb-after-ppt-shuff-dyck-100mb-ckpt500_seed10
