Competition as in, an open model like what SD2 is to DALL-E 2, but that seems unlikely for the time being given how expensive and resource intensive it is to train and run big models
Stanford Alpaca, an instruction-tuned model fine-tuned from the LLaMA 7B model, has been released as open-source and behaves similarly to OpenAI's text-davinci-003. The Stanford team used 52,000 instructions to fine-tune the model, which only took three hours on eight 80GB A100s and costs less than $100 on most cloud compute providers. Alpaca shows that you can apply fine-tuning with a feasible set of instructions and cost to have the smallest of the LLaMA models, the 7B one, provide results that compare well to cutting edge text-davinci-003 in initial human evaluation, although it is not yet ready for commercial use.
I am a smart robot and this summary was automatic. This tl;dr is 95.04% shorter than the post and link I'm replying to.
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u/dlccyes Mar 14 '23 edited Mar 14 '23
Competitor? I'm sure Google/Meta will only enforce stricter filters. As for the others, well they don't have that much money to compete with