# Instruction Tuning – Axolotl

# Instruction Tuning

Instruction tuning formats for supervised fine-tuning.

## alpaca

instruction; input(optional)

    data.jsonl

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

## jeopardy

question and answer

    data.jsonl

    {"question": "...", "category": "...", "answer": "..."}

## oasst

instruction

    data.jsonl

    {"INSTRUCTION": "...", "RESPONSE": "..."}

## gpteacher

instruction; input(optional)

    data.jsonl

    {"instruction": "...", "input": "...", "response": "..."}

## reflection

instruction with reflect; input(optional)

    data.jsonl

    {"instruction": "...", "input": "...", "output": "...", "reflection": "...", "corrected": "..."}

## explainchoice

question, choices, (solution OR explanation)

    data.jsonl

    {"question": "...", "choices": ["..."], "solution": "...", "explanation": "..."}

## concisechoice

question, choices, (solution OR explanation)

    data.jsonl

    {"question": "...", "choices": ["..."], "solution": "...", "explanation": "..."}

## summarizetldr

article and summary

    data.jsonl

    {"article": "...", "summary": "..."}

## alpaca_chat

basic instruct for alpaca chat

    data.jsonl

    {"instruction": "...", "input": "...", "response": "..."}

## alpaca_chat.load_qa

question and answer for alpaca chat

    data.jsonl

    {"question": "...", "answer": "..."}

## alpaca_chat.load_concise

question and answer for alpaca chat, for concise answers

    data.jsonl

    {"instruction": "...", "input": "...", "response": "..."}

## alpaca_chat.load_camel_ai

question and answer for alpaca chat, for load_camel_ai

    data.jsonl

    {"message_1": "...", "message_2": "..."}

## alpaca_w_system.load_open_orca

support for open orca datasets with included system prompts, instruct

    data.jsonl

    {"system_prompt": "...", "question": "...", "response": "..."}

## context_qa

in context question answering from an article

    data.jsonl

    {"article": "...", "question": "...", "answer": "..."}

## context_qa.load_v2

in context question answering (alternate)

    data.jsonl

    {"context": "...", "question": "...", "answer": "..."}

## context_qa.load_404

in context question answering from an article, with default response for no answer from context

    data.jsonl

    {"article": "...", "unanswerable_question": "..."}

## creative_acr.load_answer

instruction and revision

    data.jsonl

    {"instruction": "...", "revision": "..."}

## creative_acr.load_critique

critique

    data.jsonl

    {"scores": "...", "critiques": "...", "instruction": "...", "answer": "..."}

## creative_acr.load_revise

critique and revise

    data.jsonl

    {"scores": "...", "critiques": "...", "instruction": "...", "answer": "...", "revision": "..."}

## metharme

instruction, adds additional eos tokens

    data.jsonl

    {"prompt": "...", "generation": "..."}

## How to add custom prompt format

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.