Scaling Embedding Layers in Language Models — mentioned by ankit219

Tue, 20 May 2025 20:17:55 GMT

You can read this for a comprehensive deep dive. https://arxiv.org/pdf/2502.01637 At a very high level, instead of having embeddings at the input layers, this method keeps the embeddings at the layer level. That is every transformer layer would have its own set of learnable embedding vectors that are used to modify the processed hidden states flowing through the network. Mostly, the embeddings are precomputed and stored separately. They are queried at inference time and has very low latency, so you can get comparable performance with half the RAM. (i am not exactly sure how 3n is doing it…

Paper and discussion history. A mention is not an endorsement.

Scaling Embedding Layers in Language Models · HackerPapers discussions

Scaling Embedding Layers in Language Models — mentioned by ankit219