ai21labs

This is a tiny Jamba model used for development, debugging and experimentation over the Jamba architecture. It has 319M parameters (instead of 52B in Jamba 1.5 Mini (and Jamba v0.1) and 398B in Jamba 1.5 Large), and was trained on ~40B tokens. It is great for use in unittests since it is a small model (doesn't take long to download) that has valid and non-random outputs. Yet, it did not undergo extensive training and should not be expected to generate high-quality text.

This is a tiny Jamba reward model used for development, debugging and experimentation over the Jamba architecture. It has 319M parameters (instead of 52B in Jamba 1.5 Mini (and Jamba v0.1) and 398B in Jamba 1.5 Large), and was trained on ~40B tokens. This model was created for unit testing purposes, by turning the first three rows of Jamba-tiny-dev's LM Head into a 3-attribute reward head. The bias was set to [1000, -1000, 0], so the outputs will be in that ballpark. Due to the way it was created, this model does not aim to provide value as a reward model.

AI21’s Jamba Reasoning 3B is a top-performing reasoning model that packs leading scores on intelligence benchmarks and highly-efficient processing into a compact 3B build. Read the full blog post h...

This is a tiny, dummy version of Jamba, used for debugging and experimentation over the Jamba architecture. It has 128M parameters (instead of 52B), and is initialized with random weights and did not undergo any training.