JointEmbLLM
7.2
A framework to simplify the implementation and experimentation with joint embedding prediction models, inspired by LeCunn’s leJEPA paper. It will focus on streamlining the replacement of traditional tokenizers in LLMs with joint embeddings.
200h
mvp estimate
7.2
viability grade
12
views
technology stack
Python
Difficult
PyTorch
inspired by
Exploring joint embedding models to improve LLMs.