3 ms·
I know. The important thing is how the inference works on them.
by astrange 2y ago
I know. The important thing is how the inference works on them.
- HarHarVeryFunny 2y agoBut we're discussing a training technique, that explicitly takes advantage of the continuous (and embedding vs token probability) representations ... You could quantize a model like this after training, as usual, but that's irrelevant.
- astrange 2y agoThe paper title is "Training Large Language Models to Reason in a Continuous Latent Space". It's true it says training in the title, but the goal (reasoning in continuous space) happens at inference time.