conjecTech
Joined 14 years ago
Joined 14 years ago
I anticipate we will see something similar with intelligence. There is probably headroom to consume 100x as much intelligence in R&D. But that isn't most of the economy. Will run of the mill service jobs increase their use of intelligence by enough to offset the effect of cheaper prices? I think that's the real question.
- Did you train the encoder & decoder together or separately? It would be nice to have the encoder representation be compatible with the existing whisper implementation since it would mean you could swap your implementation into models where its used as a component, like in the recent Voxtral model. I'd imagine it also might make training a bit faster as well.
- Did you consider training the turbo model as well?
Here(https://github.com/openai/whisper/blob/main/whisper/model.py...) is the relevant code in the whisper repo. You'd just need to change the for loop to an enumerate and subsample the context along its length at the point you want. I believe it would be:
for i, block in enumerate(self.blocks): x = block(x) if i==4: x = x[,,::2]