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The paper states it was instruction fine tuned with synthetic data (LLM generated instructions) ala another paper (“Unnatural Instructions: Tuning Language Mode

The paper states it was instruction fine tuned with synthetic data (LLM generated instructions) ala another paper (“Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor”). The github repo associated with that paper is linked below. It links to the paper on arxiv, but also has some data in the repo. https://github.com/orhonovich/unnatural-instructions https://github.com/orhonovich/unnatural-instructions

ilaksh 3y ago
Maybe they used GPT-4 to train it. OpenAI terms of use don't allow that to be released commercially.
- nkohari 3y ago
  This is the most likely explanation for both why they wouldn't release it and wouldn't explain why.
- nabakin 3y ago
  I've seen this argued a lot but is it fact? OpenAI was able to train on data from other platforms and surely, those platforms weren't letting their data go if they could help it. Unless some new laws have been passed, I don't think OpenAI can legally prevent others from using their data to train models. OpenAI can't have their cake and eat it too. After all, any content generated by AI can't be copyrighted.
  - lhl 3y ago
    It is indeed a fact that OpenAI's Terms of Use do state that you can't use their service to develop competing models: Section 2.c.iii - https://openai.com/policies/terms-of-use https://openai.com/policies/terms-of-use Now of course, the terms are not the law (so don't govern the use of the generated data by any third party), they are an agreement between two parties. If you did click "agree" then that's a binding agreement and there could be legal/contractual repercussions (some of which are outlined in the terms).
    - haldujai 3y ago
      That seems like a likely explanation, probably won't get into legal trouble for using an OpenAI model for a research paper but redistributing said model may be upsetting enough for OpenAI trigger a legal challenge. Unnatural language used davinci-002 although that was a while ago, they only say "similarly" in this paper and don't specify what they used. I can't see a reason why they wouldn't be releasing it if the unnatural prompts were generated by LLaMA2-family. In any case, replicating this training seems trivial and very cheap compute-wise for anyone who wanted to do it.

ilaksh 3y ago

Maybe they used GPT-4 to train it. OpenAI terms of use don't allow that to be released commercially.

nkohari 3y ago
This is the most likely explanation for both why they wouldn't release it and wouldn't explain why.
nabakin 3y ago
I've seen this argued a lot but is it fact? OpenAI was able to train on data from other platforms and surely, those platforms weren't letting their data go if they could help it. Unless some new laws have been passed, I don't think OpenAI can legally prevent others from using their data to train models. OpenAI can't have their cake and eat it too. After all, any content generated by AI can't be copyrighted.
- lhl 3y ago
  It is indeed a fact that OpenAI's Terms of Use do state that you can't use their service to develop competing models: Section 2.c.iii - https://openai.com/policies/terms-of-use https://openai.com/policies/terms-of-use Now of course, the terms are not the law (so don't govern the use of the generated data by any third party), they are an agreement between two parties. If you did click "agree" then that's a binding agreement and there could be legal/contractual repercussions (some of which are outlined in the terms).
  - haldujai 3y ago
    That seems like a likely explanation, probably won't get into legal trouble for using an OpenAI model for a research paper but redistributing said model may be upsetting enough for OpenAI trigger a legal challenge. Unnatural language used davinci-002 although that was a while ago, they only say "similarly" in this paper and don't specify what they used. I can't see a reason why they wouldn't be releasing it if the unnatural prompts were generated by LLaMA2-family. In any case, replicating this training seems trivial and very cheap compute-wise for anyone who wanted to do it.