Large language models (LLMs) such as GPT-3, OPT, and LLaMA have demonstrated remarkable accuracy in a wide range of tasks.
In summary, our study introduces an innovative PTQ method for ProteinLMs, addressing specific quantization challenges and potentially leading to the development of more efficient ProteinLMs with significant implications for various protein-related applications.
With the development of online business, customer service agents gradually play a crucial role as an interface between the companies and their customers.
Building robust and general dialogue models for spoken conversations is challenging due to the gap in distributions of spoken and written data.
In the Chinese medical insurance industry, the assessor's role is essential and requires significant efforts to converse with the claimant.