# Causal Language Model

A large language model in the medical field developed by MoAData, trained on a self-made medical dataset using the DPO method.

Mamba is an efficient sequence model compatible with transformers, with 790 million parameters, suitable for causal language modeling tasks.

OpenCALM is a 3B-parameter version of the decoder-only language model series developed by CyberAgent, pretrained on Japanese datasets.

Pythia-1B is a language model specialized for interpretability research developed by EleutherAI, belonging to the 1-billion-parameter version in the Pythia suite, trained on The Pile dataset.

Pythia-6.9B is a large-scale language model developed by EleutherAI, part of the Pythia scalable suite, specifically designed to facilitate interpretability research.

Pythia is a series of causal language models developed by EleutherAI, specifically designed for interpretability research. It includes 8 model sizes ranging from 70 million to 12 billion parameters, providing 154 training checkpoints.

Pythia-1.4B is a 1.2 billion parameter causal language model developed by EleutherAI, part of the Pythia scale suite, specifically designed for interpretability research.

A GPT-2 language model fine-tuned on Skillet band lyrics for generating similar style text content