metadata
dataset_info:
features:
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dtype: string
- name: text
dtype: string
- name: url
dtype: string
- name: date
dtype: timestamp[ns, tz=UTC]
- name: dump
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- name: language_score
dtype: float64
- name: minhash_cluster_size
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- name: top_langs
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- name: topic_class_1
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splits:
- name: train
num_bytes: 225675034950
num_examples: 54128784
download_size: 131804901421
dataset_size: 225675034950
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
FineWeb2-Ro-BERT
FineWeb2-Ro-BERT is a large-scale pretraining dataset in the Romanian language. The data is derived from FineWeb2 and annotated using a bert architecture for signals such as educational quality or topic. More details can be found here.
Key Features
- Massive Scale: Contains approximately 54.1M rows (documents or sequences), providing comprehensive linguistic coverage for training robust Romanian embeddings and encoders.
Usage
You can load this dataset using the Hugging Face datasets library:
from datasets import load_dataset
dataset = load_dataset("OpenLLM-Ro/fineweb2-ro-bert", split="train")