Datasets:
Tasks:
Text Generation
Modalities:
Text
Formats:
parquet
Languages:
Thai
Size:
10K - 100K
Tags:
instruct-fellow
License:
language: | |
- th | |
license: cc0-1.0 | |
size_categories: | |
- 10K<n<100K | |
task_categories: | |
- text-generation | |
- text2text-generation | |
pretty_name: i | |
dataset_info: | |
features: | |
- name: inputs | |
dtype: string | |
- name: targets | |
dtype: string | |
splits: | |
- name: train | |
num_bytes: 10132750 | |
num_examples: 16194 | |
- name: validation | |
num_bytes: 1118295 | |
num_examples: 1777 | |
- name: test | |
num_bytes: 1240521 | |
num_examples: 1965 | |
download_size: 3093175 | |
dataset_size: 12491566 | |
tags: | |
- instruct-fellow | |
configs: | |
- config_name: default | |
data_files: | |
- split: train | |
path: data/train-* | |
- split: validation | |
path: data/validation-* | |
- split: test | |
path: data/test-* | |
wisesight_sentiment_prompt is the instruct fellow dataset for sentiment Thai text by prompt. It can use fine-tuning model. | |
- inputs: Prompt | |
- targets: Text targets that AI should answer. | |
**Template** | |
``` | |
Inputs: จำแนกประโยคต่อไปนี้เป็นคำถามหรือข้อความเชิงบวก/เป็นกลาง/เชิงลบ:\n{text} | |
targets: ประโยคที่กำหนดสามารถจำแนกข้อความได้เป็นข้อความ{category} | |
``` | |
category | |
- คำถาม: question | |
- เชิงบวก: positive | |
- เป็นกลาง: neutral | |
- เชิงลบ: negative | |
Notebook that used create this dataset: [https://github.com/PyThaiNLP/support-aya-datasets/blob/main/sentiment-analysis/wisesight_sentiment.ipynb](https://github.com/PyThaiNLP/support-aya-datasets/blob/main/sentiment-analysis/wisesight_sentiment.ipynb) | |
Wisesight Sentiment Corpus: Social media messages in Thai language with sentiment category (positive, neutral, negative, question) | |
* Released to public domain under Creative Commons Zero v1.0 Universal license. | |
* Size: 26,737 messages | |
* Language: Central Thai | |
* Style: Informal and conversational. With some news headlines and advertisement. | |
* Time period: Around 2016 to early 2019. With small amount from other period. | |
* Domains: Mixed. Majority are consumer products and services (restaurants, cosmetics, drinks, car, hotels), with some current affairs. | |
See more: [wisesight_sentiment](https://huggingface.co/datasets/wisesight_sentiment). | |
PyThaiNLP |