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Datasets:
rishiraj
/
portuguesechat

Tasks:
Text Generation
Modalities:
Text
Formats:
parquet
Languages:
Portuguese
Size:
10K - 100K
ArXiv:
Libraries:
Datasets
pandas
License:
Dataset card Viewer Files Community
1
portuguesechat
File size: 3,360 Bytes 
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---
dataset_info:
  features:
  - name: prompt
    dtype: string
  - name: prompt_id
    dtype: string
  - name: messages
    list:
    - name: content
      dtype: string
    - name: role
      dtype: string
  - name: category
    dtype: string
  - name: text
    dtype: string
  splits:
  - name: train
    num_bytes: 30628039
    num_examples: 9500
  - name: test
    num_bytes: 1644450
    num_examples: 500
  download_size: 19873853
  dataset_size: 32272489
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
task_categories:
- conversational
- text-generation
language:
- pt
pretty_name: Portuguese Chat
license: cc-by-nc-4.0
---
# Dataset Card for Portuguese Chat

We know that current English-first LLMs don’t work well for many other languages, both in terms of performance, latency, and speed. Building instruction datasets for non-English languages is an important challenge that needs to be solved.

Dedicated towards addressing this problem, I release 3 new datasets [rishiraj/portuguesechat](https://huggingface.co/datasets/rishiraj/portuguesechat/), [rishiraj/bengalichat](https://huggingface.co/datasets/rishiraj/bengalichat/) & [rishiraj/hindichat](https://huggingface.co/datasets/rishiraj/hindichat/) of 10,000 instructions and demonstrations each. This data can be used for supervised fine-tuning (SFT) to make language multilingual models follow instructions better.

### Dataset Summary

[rishiraj/portuguesechat](https://huggingface.co/datasets/rishiraj/portuguesechat/) was modelled after the instruction dataset described in OpenAI's [InstructGPT paper](https://huggingface.co/papers/2203.02155), and is translated from [HuggingFaceH4/no_robots](https://huggingface.co/datasets/HuggingFaceH4/no_robots/) which comprised mostly of single-turn instructions across the following categories:

| Category   |   Count |
|:-----------|--------:|
| Generation |    4560 |
| Open QA    |    1240 |
| Brainstorm |    1120 |
| Chat       |     850 |
| Rewrite    |     660 |
| Summarize  |     420 |
| Coding     |     350 |
| Classify   |     350 |
| Closed QA  |     260 |
| Extract    |     190 |

### Languages

The data in [rishiraj/portuguesechat](https://huggingface.co/datasets/rishiraj/portuguesechat/) are in Portuguese (BCP-47 pt).

### Data Fields

The data fields are as follows:

* `prompt`: Describes the task the model should perform.
* `prompt_id`: A unique ID for the prompt.
* `messages`: An array of messages, where each message indicates the role (system, user, assistant) and the content.
* `category`: Which category the example belongs to (e.g. `Chat` or `Coding`).
* `text`: Content of `messages` in a format that is compatible with dataset_text_field of SFTTrainer.

### Data Splits

|               | train_sft | test_sft |
|---------------|------:| ---: |
| portuguesechat  | 9500 | 500 |

### Licensing Information

The dataset is available under the [Creative Commons NonCommercial (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/legalcode).

### Citation Information

```
@misc{portuguesechat,
  author = {Rishiraj Acharya},
  title = {Portuguese Chat},
  year = {2023},
  publisher = {Hugging Face},
  journal = {Hugging Face repository},
  howpublished = {\url{https://huggingface.co/datasets/rishiraj/portuguesechat}}
}
```