**eformer** (EasyDel Former) is a utility library designed to simplify and enhance the development of machine learning models using JAX. It provides a collection of tools for sharding, custom PyTrees, quantization, mixed precision training, and optimized operations, making it easier to build and scale models efficiently.
- **Mixed Precision Training (`mpric`)**: Advanced mixed precision utilities supporting float8, float16, and bfloat16 with dynamic loss scaling.
- **Sharding Utilities (`escale`)**: Tools for efficient sharding and distributed computation in JAX.
- **Custom PyTrees (`jaximus`)**: Enhanced utilities for creating custom PyTrees and `ArrayValue` objects, updated from Equinox.
- **Custom Calling (`callib`)**: A tool for custom function calls and direct integration with Triton kernels in JAX.
- **Optimizer Factory**: A flexible factory for creating and configuring optimizers like AdamW, Adafactor, Lion, and RMSProp.
- **Custom Operations and Kernels**:
- Flash Attention 2 for GPUs/TPUs (via Triton and Pallas).
- 8-bit and NF4 quantization for efficient model.
- Many others to be added.
- **Quantization Support**: Tools for 8-bit and NF4 quantization, enabling memory-efficient model deploymen