README.md

metadata

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:

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 page for details.