Conversation

Conversation format for supervised fine-tuning.

Formats

sharegpt

conversations where from is human/gpt. (optional: first row with role system to override default system prompt)

data.jsonl

{"conversations": [{"from": "...", "value": "..."}]}

Note: type: sharegpt opens a special config conversation: that enables conversions to many Conversation types. See the docs for all config options.

pygmalion

data.jsonl

{"conversations": [{"role": "...", "value": "..."}]}

sharegpt.load_role

conversations where role is used instead of from

data.jsonl

{"conversations": [{"role": "...", "value": "..."}]}

sharegpt.load_guanaco

conversations where from is prompter assistant instead of default sharegpt

data.jsonl

{"conversations": [{"from": "...", "value": "..."}]}

sharegpt_jokes

creates a chat where bot is asked to tell a joke, then explain why the joke is funny

data.jsonl

{"conversations": [{"title": "...", "text": "...", "explanation": "..."}]}

How to add custom prompts for instruction-tuning

For a dataset that is preprocessed for instruction purposes:

data.jsonl

{"input": "...", "output": "..."}

You can use this example in your YAML config:

config.yaml

datasets:
  - path: repo
    type:
      system_prompt: ""
      field_system: system
      field_instruction: input
      field_output: output
      format: "[INST] {instruction} [/INST]"
      no_input_format: "[INST] {instruction} [/INST]"

See full config options under here.