Add paramax

Author: danielward27

README.md

@@ -89,7 +89,8 @@ If you found this library to be useful in academic work, then please cite: ([arX
 **Deep learning**  
 [Optax](https://github.com/deepmind/optax): first-order gradient (SGD, Adam, ...) optimisers.  
 [Orbax](https://github.com/google/orbax): checkpointing (async/multi-host/multi-device).  
-[Levanter](https://github.com/stanford-crfm/levanter): scalable+reliable training of foundation models (e.g. LLMs).  
+[Levanter](https://github.com/stanford-crfm/levanter): scalable+reliable training of foundation models (e.g. LLMs).
+[paramax](https://github.com/danielward27/paramax): parameterizations and constraints for PyTrees.
 
 **Scientific computing**  
 [Diffrax](https://github.com/patrick-kidger/diffrax): numerical differential equation solvers.  

docs/index.md

@@ -79,6 +79,7 @@ If this quick start has got you interested, then have a read of [All of Equinox]
 [Optax](https://github.com/deepmind/optax): first-order gradient (SGD, Adam, ...) optimisers.  
 [Orbax](https://github.com/google/orbax): checkpointing (async/multi-host/multi-device).  
 [Levanter](https://github.com/stanford-crfm/levanter): scalable+reliable training of foundation models (e.g. LLMs).  
+[paramax](https://github.com/danielward27/paramax): parameterizations and constraints for PyTrees.
 
 **Scientific computing**  
 [Diffrax](https://github.com/patrick-kidger/diffrax): numerical differential equation solvers.