Finetuning Transformers with JAX + Haiku
A practical, code-first look at DeepMind's new haiku library.
A Survey of Long-Term Context in Transformers
Exploring 6 noteworthy approaches for incorporating longer-term context in transformer models.
Rationale Informed Classification
Leveraging annotator rationales for more interpretable and sample efficient classification.
A Deep Dive into the Reformer
Time and memory efficient alternatives to vanilla transformers through locality sensitive hashing and reversible layers.
A First Look at JAX
Put on your metaphorical safety goggles and start building something weird with JAX.
ROC Curves: Intuition Through Visualization
Building intuition for Receiving Operator Characterstic (ROC) curves and what they measure through visualization.
Einsum Extensions: A Wish List for Readable Matrix Ops
Musings on extensions to einsum notation for more readable machine learning code.
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