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They add new data to the existing base model via continuous pre-training. You save on pre-training, the next token prediction task, but still have to re-run mid
by rockinghigh 10mo ago
They add new data to the existing base model via continuous pre-training. You save on pre-training, the next token prediction task, but still have to re-run mid and post training stages like context length extension, supervised fine tuning, reinforcement learning, safety alignment ...
- astrange 10mo agoContinuous pretraining has issues because it starts forgetting the older stuff. There is some research into other approaches.