Release StudyBench on Hugging Face
Nadie ha tomado este issue todavía.
Evaluación
- Dificultad
- 5/5
- Tiempo estimado
- Más de una semana
- Aptitud para principiantes
- 25/100
- Tipo de issue
- Nueva funcionalidad
- Claridad
- Necesita aclaración
- Estado de actividad
- Activo
- Stack tecnológico
- huggingface, python
- Área
- data, machine-learning
Línea de trabajo
Start by reviewing the StudyBench dataset in the GitHub repository and the Hugging Face Datasets loading guide linked in the issue. The issue names no repository files or tests. Done would mean the dataset is hosted on Hugging Face and linked to the paper page, subject to the authors' agreement.
Escrito por el modelo de indexación a partir del texto del issue.
Descripción
Hi @thunlp 🤗
I'm Niels and work as part of the open-source team at Hugging Face. I discovered your work on Arxiv (https://arxiv.org/abs/2609.00787) and was wondering whether you would like to submit it to hf.co/papers to improve its discoverability. If you are one of the authors, you can submit it at https://arxiv.org/abs/2609.00787
The paper page lets people discuss about your paper and lets them find artifacts about it (your dataset for instance),
you can also claim the paper as yours which will show up on your public profile at HF, add Github and project page URLs.
Would you like to host the StudyBench dataset on https://huggingface.co/datasets?
I see you've released the dataset as part of your Github repository. Hosting on Hugging Face will give you more visibility/enable better discoverability, and will also allow people to do:
from datasets import load_dataset
dataset = load_dataset("your-hf-org-or-username/studybench")
If you're down, leaving a guide here: https://huggingface.co/docs/datasets/loading.
We also support Webdataset, useful for image/video datasets: https://huggingface.co/docs/datasets/en/loading#webdataset.
Besides that, there's the dataset viewer which allows people to quickly explore the first few rows of the data in the browser.
After uploaded, we can also link the datasets to the paper page (read here) so people can discover your work.
Let me know if you're interested/need any guidance.
Kind regards,
Niels
- Lenguaje dominante
- Python
- Estrellas
- 8
- Forks
- 1
- Métricas de merge de PR
- Sin PR fusionados en 30 d
Preparar el entorno
Este proyecto no incluye contenedor de desarrollo, Dockerfile ni guía de contribución, así que la configuración corre por tu cuenta: empieza por su README y consulta nuestra guía para la primera contribución para los pasos generales.
Primeros pasos
- Lee el issue completo y luego la guía de contribución del proyecto.
- Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
- Haz un fork del repositorio y trabaja en una rama.
- Abre un pull request que haga referencia al número del issue.
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