This is my take on implementing the Self-Instruct paper. The approach is quite heavily modified, and does not use any human-generated seeds.
This updated implementation supports either the /v1/completions endpoint or /v1/chat/completions, which is particularly useful in that it supports gpt-4 and gpt-3.5-turbo (which is 1/10 the cost of text-davinci-003).
- support for either /v1/completions or /v1/chat/completions APIs (which allows gpt-3.5-turbo instead of text-davinci-003, as well as gpt-4 if you have access)
- support for custom topics list, custom topic generation prompt, or completely random topics
- in-memory vector db (Chroma) for similarity comparison, which is much faster than calculating rouge score for each generated instruction
- (seemingly) better prompts, which includes injection of random topics to relate the instructions to, which creates much more diverse synthetic instructions
- asyncio producers with configurable batch size
- several "instructors", each targetting specific use-cases, such as Orca style reasoning/math, role playing, etc.
- tries to ensure the context, if provided, is relevant to the topic and contains all the information that would be necessary to respond to the instruction, and nost just a link to article/etc.
- generally speaking, this implementation tries to reduce some of the noise
To better accomodate the plethora of options, the configuration has been moved to a YAML config file.
Please create a copy of example-config.yaml and configure as desired.
Once you have the desired configuration, run:
airoboros generate-instructions --config-path /path/to/config.yaml
Again, this is now all YAML configuration based! Please create a customized version of the YAML config file, then run:
airoboros generate-topics --config-path /path/to/config.yaml
You can override the topic_prompt string in the configuration to use a different topic generation prompt.
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Latest version (2.0 / m2.0 datasets)
- airoboros-l2-7b-gpt4-2.0
- airoboros-l2-7b-gpt4-m2.0
- airoboros-l2-13b-gpt4-2.0
- airoboros-l2-13b-gpt4-m2.0
Previous generation (1.4.1 dataset)
Latest version (2.0 / m2.0 datasets)
Previous generation (1.4.1 dataset)
- airoboros-65b-gpt4-1.4
- airoboros-33b-gpt4-1.4
- airoboros-13b-gpt4-1.4
- airoboros-7b-gpt4-1.4
- older versions on HF as well
- airoboros-gpt-3.5-turbo
- airoboros-gpt4
- airoboros-gpt4-1.1
- airoboros-gpt4-1.2
- airoboros-gpt4-1.3
- airoboros-gpt4-1.4
- airoboros-gpt4-2.0 (June only GPT4)
- airoboros-gpt4-m2.0 (recommended)
Scripts for fine-tuning various models using the self-instruct (and human-generated) prompts.