72 lines
1.7 KiB
Plaintext
72 lines
1.7 KiB
Plaintext
---
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title: Conversation
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description: Conversation format for supervised fine-tuning.
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order: 1
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---
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## Formats
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### sharegpt
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conversations where `from` is `human`/`gpt`. (optional: first row with role `system` to override default system prompt)
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```{.json filename="data.jsonl"}
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{"conversations": [{"from": "...", "value": "..."}]}
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```
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Note: `type: sharegpt` opens a special config `conversation:` that enables conversions to many Conversation types. See [the docs](../docs/config.qmd) for all config options.
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### pygmalion
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```{.json filename="data.jsonl"}
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{"conversations": [{"role": "...", "value": "..."}]}
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```
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### sharegpt.load_role
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conversations where `role` is used instead of `from`
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```{.json filename="data.jsonl"}
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{"conversations": [{"role": "...", "value": "..."}]}
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```
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### sharegpt.load_guanaco
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conversations where `from` is `prompter` `assistant` instead of default sharegpt
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```{.json filename="data.jsonl"}
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{"conversations": [{"from": "...", "value": "..."}]}
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```
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### sharegpt_jokes
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creates a chat where bot is asked to tell a joke, then explain why the joke is funny
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```{.json filename="data.jsonl"}
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{"conversations": [{"title": "...", "text": "...", "explanation": "..."}]}
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```
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## How to add custom prompts for instruction-tuning
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For a dataset that is preprocessed for instruction purposes:
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```{.json filename="data.jsonl"}
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{"input": "...", "output": "..."}
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```
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You can use this example in your YAML config:
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```{.yaml filename="config.yaml"}
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datasets:
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- path: repo
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type:
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system_prompt: ""
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field_system: system
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field_instruction: input
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field_output: output
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format: "[INST] {instruction} [/INST]"
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no_input_format: "[INST] {instruction} [/INST]"
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```
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See full config options under [here](../docs/config.qmd).
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