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Found 3 papers, 1 papers with code
HLSTransform: Energy-Efficient Llama 2 Inference on FPGAs Via High Level Synthesis
Graphics Processing Units (GPUs) have become the leading hardware accelerator for deep learning applications and are used widely in training and inference of transformers; transformers have achieved state-of-the-art performance in many areas of machine learning and are especially used in most modern Large Language Models (LLMs).
WorldCoder, a Model-Based LLM Agent: Building World Models by Writing Code and Interacting with the Environment
We give a model-based agent that builds a Python program representing its knowledge of the world based on its interactions with the environment.
Toward Trustworthy Neural Program Synthesis
We develop an approach to estimate the probability that a program sampled from a large language model is correct.
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