---
dataset_info:
  features:
  - name: prompt
    dtype: string
  - name: response
    dtype: string
  splits:
  - name: train
    num_bytes: 194746016
    num_examples: 418357
  download_size: 89077742
  dataset_size: 194746016
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: odc-by
task_categories:
- text-generation
language:
- en
size_categories:
- 100K<n<1M
---


# fingpt - all - prompt/response format


loaded/created via:


```py
from datasets import load_dataset

dataset_names = [
    "FinGPT/fingpt-sentiment-train",
    "FinGPT/fingpt-fiqa_qa",
    "FinGPT/fingpt-headline-cls",
    "FinGPT/fingpt-convfinqa",
    "FinGPT/fingpt-finred-cls",
    "FinGPT/fingpt-ner",
    "FinGPT/fingpt-finred",
    "FinGPT/fingpt-sentiment-cls",
    "FinGPT/fingpt-ner-cls",
    "FinGPT/fingpt-finred-re",
    "FinGPT/fingpt-headline"
]
ds_list = []

for ds_name in dataset_names:
    ds = load_dataset(ds_name, split="train")
    ds = ds.map(lambda x: {'source': ds_name}, num_proc=8)
    ds_list.append(ds)

ds_list
```

See [fingpt](https://huggingface.co/FinGPT) page for details.