# Efficient language model

BitNet b1.58 is a large language model with 1.58-bit quantization. It reduces the computational resource requirements by lowering the weight precision while maintaining performance close to that of a full-precision model.

OpenELM is a set of open-source and efficient language models. It adopts a hierarchical parameter allocation strategy to improve model accuracy and includes pre-trained and instruction-tuned versions with 270 million to 3 billion parameters.

OpenELM is a set of open-source efficient language models that use a hierarchical scaling strategy to efficiently allocate parameters in each layer of the Transformer model, thereby improving model accuracy.