gabtan99/dialogpt-tagalog-medium
Text Generation
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Updated
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7
Datasets:
category
stringclasses 8
values | conversations
list |
|---|---|
body-and-fitness | [{"replies":[{"replies":[],"text":""},{"replies":[],"text":"Sample computation using for an individu(...TRUNCATED) |
food-and-drinks | [{"replies":[{"replies":[],"text":"7deadlyjeans the japanese people are cool. They gave us anime, so(...TRUNCATED) |
health-and-wellness | [{"replies":[],"text":"All forms of secondhand smoke can damage lungs. Make your time at home as saf(...TRUNCATED) |
home-and-garden | [{"replies":[{"replies":[],"text":"Mukhang ok yung jao bulders."},{"replies":[{"replies":[],"text":"(...TRUNCATED) |
small-talk | [{"replies":[{"replies":[],"text":"Tapatalk would be nice."},{"replies":[],"text":"Mobile browsing m(...TRUNCATED) |
style-and-fashion | [{"replies":[{"replies":[],"text":"The convenience of checking out clothes and sizes makes me shop o(...TRUNCATED) |
travel-and-leisure | [{"replies":[{"replies":[],"text":"1."},{"replies":[],"text":"2."},{"replies":[],"text":"3."},{"repl(...TRUNCATED) |
visas-and-immigration | [{"replies":[{"replies":[],"text":"Kung government employee ka at wala kang authority to travel, wag(...TRUNCATED) |
YAML Metadata
Warning:
The task_categories "sequence-modeling" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, text2text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, other
PinoyExchange (PEx) Conversations Dataset
Summary
PEx Conversations is a dataset composed of collected threads from PinoyExchange.com (Consisting of Tagalog, English, or Taglish responses).
The corpus consists of 45K total scraped threads from 8 subforums. The data only consists of the user message which means any images, videos, links, or any embdedded html are not collected in the scraping process. All characters have been transliterated to its closest ASCII representation, and unicode errors were fixed.
Format
The data is categorized per category. The objects in the list is composed of:
- category - the category of the threads
- conversations - the list of threads
The threads inside conversations have recursive structure consisting of the following:
- text - This is the response/reply/prompt
- replies - This is a list of the replies to this prompt. The replies inside the list has a structure with the same text and replies component.
Subforum percentages
The amount of data per subforum are as follows:
- Small Talk - 5K conversations with 1.16M utterances
- Food & Drinks - 8.2K conversations with 273K utterances
- Health & Wellness - 6.3K conversations with 93K utterances
- Body & Fitness - 3.9K conversations with 94K utterances
- Home & Garden - 3.6K conversations with 71K utterances
- Style & Fashion - 9.7K conversations with 197K utterances
- Travel & Leisure - 7.3K conversations with 431K utterances
- Visas & Immigration - 1.1K conversations with 99K utterances
Model Research
- Downloads last month
- 156
Size of downloaded dataset files:
658 MB
Size of the auto-converted Parquet files:
239 MB
Number of rows:
8
Models trained or fine-tuned on gabtan99/pex-conversations