Datasets:
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---
language:
- en
- pt
- de
- fr
- es
license: odc-by
size_categories:
- 10M<n<100M
source_datasets: OpenCo7/UpVoteWeb
task_categories:
- text-generation
- feature-extraction
- image-to-text
- text-to-image
- fill-mask
dataset_info:
- config_name: default
features:
- name: post_id
dtype: string
- name: text
dtype: string
- name: url
dtype: string
- name: date
dtype: string
- name: author
dtype: string
- name: subreddit
dtype: string
- name: score
dtype: int64
- name: token_count
dtype: int64
- name: language
dtype: string
- name: language_score
dtype: float64
- name: media_urls
dtype: string
splits:
- name: train
num_bytes: 9259550876
num_examples: 16056485
download_size: 5885641617
dataset_size: 9259550876
- config_name: eduscore-1
features:
- name: post_id
dtype: string
- name: text
dtype: string
- name: url
dtype: string
- name: date
dtype: string
- name: author
dtype: string
- name: subreddit
dtype: string
- name: eduscore
dtype: float64
- name: token_count
dtype: int64
- name: language
dtype: string
- name: language_score
dtype: float64
- name: media_urls
dtype: string
- name: eduscore_int
dtype: int64
splits:
- name: train
num_bytes: 1106382730.0
num_examples: 661861
download_size: 702006131
dataset_size: 1106382730.0
- config_name: eduscored
features:
- name: post_id
dtype: string
- name: text
dtype: string
- name: url
dtype: string
- name: date
dtype: string
- name: author
dtype: string
- name: subreddit
dtype: string
- name: eduscore
dtype: float64
- name: token_count
dtype: int64
- name: language
dtype: string
- name: language_score
dtype: float64
- name: media_urls
dtype: string
- name: eduscore_int
dtype: int64
splits:
- name: train
num_bytes: 9388002756
num_examples: 16056485
download_size: 5937232561
dataset_size: 9388002756
- config_name: en-clean
features:
- name: post_id
dtype: string
- name: text
dtype: string
- name: url
dtype: string
- name: date
dtype: string
- name: author
dtype: string
- name: subreddit
dtype: string
- name: score
dtype: int64
- name: token_count
dtype: int64
- name: language
dtype: string
- name: language_score
dtype: float64
- name: media_urls
dtype: string
splits:
- name: train
num_bytes: 7830835057
num_examples: 13019754
download_size: 4956674820
dataset_size: 7830835057
- config_name: image-dataset-sample
features:
- name: post_id
dtype: string
- name: text
dtype: string
- name: date
dtype: string
- name: author
dtype: string
- name: subreddit
dtype: string
- name: score
dtype: int64
- name: token_count
dtype: int64
- name: language
dtype: string
- name: language_score
dtype: float64
- name: image
dtype: image
splits:
- name: train
num_bytes: 97242067379.125
num_examples: 122087
download_size: 96955619502
dataset_size: 97242067379.125
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- config_name: eduscore-1
data_files:
- split: train
path: eduscore-1/train-*
- config_name: eduscored
data_files:
- split: train
path: eduscored/train-*
- config_name: en-clean
data_files:
- split: train
path: en-clean/train-*
- config_name: image-dataset-sample
data_files:
- split: train
path: image-dataset-sample/train-*
tags:
- reddit
- upvoteweb
---
# upvoteweb: posts
Posts in [upvoteweb](https://huggingface.co/datasets/OpenCo7/UpVoteWeb).
## configs
> [!IMPORTANT]
> There are several configs representing different permutations of this dataset. Load the relevant config for the task you are interested in.
Overview of configs:
- `default`: largely unfiltered/unprocessed original data
- `eduscored`: the "eduscore" predicted on the `text` column with [huggingface's trained classifier](https://hf.co/HuggingFaceFW/fineweb-edu-classifier)
- `en-clean`: filter `language` for `en` and `language_score` for > `0.6`. Run [clean-text](https://pypi.org/project/clean-text/) on the `text` col, preserving casing
- `image-dataset-sample`: filter for posts with `score` > 2000, at least one URL that points to an image. Load the first image URL into a new `image` col, and resize it to have a max dim of 2048
Pass the config name as a second fn arg when loading the dataset to load that config. For example, to load `eduscored`:
```py
from datasets import load_dataset
ds = load_dataset("BEE-spoke-data/upvoteweb-posts", "eduscored")
ds
```
## lang details
Some simple counts in `default`:
```
language
en 14745361
de 271905
es 176108
pt 138175
fr 126898
...
kv 2
tyv 1
myv 1
hif 1
lez 1
Name: count, Length: 171, dtype: int64
``` |