metadata
language:
- ro
dataset_info:
features:
- name: id
dtype: string
- name: text
dtype: string
- name: url
dtype: string
- name: date
dtype: string
- name: dump
dtype: string
- name: file_path
dtype: string
- name: language_score
dtype: float64
- name: minhash_cluster_size
dtype: int64
- name: top_langs
dtype: string
- name: output
dtype: string
- name: explanation
dtype: string
- name: int_score
dtype: string
- name: age_group
dtype: string
- name: topic
dtype: string
- name: subtopic
dtype: string
- name: format
dtype: string
splits:
- name: train
num_bytes: 5492801065
num_examples: 1058200
download_size: 2976465017
dataset_size: 5492801065
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
FineWeb2-Ro-LLM
FineWeb2-Ro-LLM is a high-quality pretraining dataset for the Romanian language. The data comes from FineWeb2 and annotated leveraging LLMs. More details can be found here.
Key Features
- High Quality: The dataset was annotated using Gemma3 12B
- Large Scale: Contains approximately 1.06M documents (rows).
- Rich Metadata: Includes detailed metadata such as quality scores (
int_score), topics, subtopics, and reasoning/explanations for the assigned quality scores.
Usage
You can load this dataset using the Hugging Face datasets library:
from datasets import load_dataset
dataset = load_dataset("OpenLLM-Ro/fineweb2-ro-llm", split="train")