metadata

language:
  - ru
size_categories:
  - 1K<n<10K
task_categories:
  - question-answering
  - text-classification
  - text-generation
pretty_name: R
dataset_info:
  features:
    - name: topic
      dtype: string
    - name: user_question
      dtype: string
    - name: assistant_answer
      dtype: string
    - name: to_doctor
      dtype: string
    - name: __index_level_0__
      dtype: int64
    - name: prompt
      dtype: string
  splits:
    - name: train
      num_bytes: 7995673.941131692
      num_examples: 3546
    - name: test
      num_bytes: 890663.0588683075
      num_examples: 395
  download_size: 3764582
  dataset_size: 8886337
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*
tags:
  - medical
  - biology
  - synthetic

Russian-language dataset of 3743 patient conversations with a medical bot in QA manner.

The training sample includes 3014 conversations;
The test sample includes 335 conversations;

Feature characteristics:

topic - medical topic
user_question - last user question
assistant_answer - ai answer according the context and topic
to_doctor - the specialty of the physician to whom the assistant referred the patient
prompt - ready prompt for fincetuning instruct phi model (adapted for using with unsloth https://github.com/unslothai/unsloth?tab=readme-ov-file)

Prompt format:

<|user|>USER QUESTION<|end|>\n<|assistant|>ASSISTANT ANSWER<|end|>

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