metadata
dataset_info:
- config_name: dedup
features:
- name: title
dtype: string
- name: description
dtype: string
- name: tags
sequence: string
- name: chapter_names
sequence: string
- name: chapter_contents
sequence: string
- name: language
dtype: string
- name: language_confidence
dtype: float64
- name: overall_nsfw_score
dtype: float64
- name: chapter_nsfw_scores
sequence: float64
splits:
- name: train
num_bytes: 601170344
num_examples: 7466
download_size: 341659219
dataset_size: 601170344
- config_name: default
features:
- name: title
dtype: string
- name: description
dtype: string
- name: tags
sequence: string
- name: chapter_names
sequence: string
- name: chapter_contents
sequence: string
- name: language
dtype: string
- name: language_confidence
dtype: float64
- name: overall_nsfw_score
dtype: float64
- name: chapter_nsfw_scores
sequence: float64
- name: overall_ai_score
dtype: float64
- name: chapter_ai_scores
sequence: float64
splits:
- name: train
num_bytes: 739774729
num_examples: 8817
download_size: 420226700
dataset_size: 739774729
configs:
- config_name: dedup
data_files:
- split: train
path: dedup/train-*
- config_name: default
data_files:
- split: train
path: data/train-*
i would not recommend relying on the nsfw scores for any language other than english (or at all for that matter)
i eventually got language detection working okay, but if you have a better solution please let me know because this still isn't great at handling wonky characters like many of these stories use