Emerging out of intensive research and development, the Arcee team is excited to release our commercial product to contextualize language models in the Arcee platform.

Arcee is excited to exit stealth with an open core to contextualize domain adapted language models (DALMs). ‍Unifying the Retriever and Generator As language modeling techniques have evolved, we have seen an increasing effectiveness in retrieval augmented generation (RAG), where the generator model is provided with relevant context documents from

Introduction: Natural Language Processing has seen remarkable advancements in recent years, enabling machines to comprehend and generate human language effectively. Two popular approaches used in NLP are RAG (Retrieval-Augmented Generation) systems and fine-tuning. In this blog post, we will delve into the strengths and weaknesses of both approaches to gain

In the rapidly evolving landscape of Generative AI, the quest for more refined and contextually aware language models has led to our development of the Domain Adapted Language Model System (DALM). This innovation promises to reshape how enterprises harness the power of language models tailored to their specific domains. In