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+1, also this is a teacher model. The implications are huge here as AWS will likely spin this into an offering like they did with their other AI products. Build
by cuuupid 4y ago
+1, also this is a teacher model. The implications are huge here as AWS will likely spin this into an offering like they did with their other AI products. Building a model downstream of GPT-3 is difficult and usually yields suboptimal results; however 20b is small enough that it would be easy to finetune this on a smaller dataset for a specific task.
You could then distill that model and end up with something that’s a fraction of the size (6b parameters for example, just under 1/3, would fit on commercial GPUs like 3090s). There are some interesting examples of this with smaller models like BERT/BART or PEGASUS in Huggingface Transformer’s seq2seq distillation examples.