Must-read Papers on Large Language Model (LLM) as Optimizers and Automatic Optimization for Prompting LLMs. Topics review optimization optimizer survey awesome-list papers optimization-algorithms large-language-models llm prompting llms Resources Readme Activity Custom properties Stars 214 stars ...
We introduce a novel population-based method for numerical optimization using LLMs called Language-Model-Based Evolutionary Optimizer (LEO). Our hypothesis is supported through numerical examples, spanning benchmark and industrial engineering problems such as supersonic nozzle shape optimization, heat ...
named_parameters() if "bias" in n) optimizer = Optimizer(params) Reparametrization: LoRa - Low-rank decomposition. Efficient, Complex to implement. def lora_linear(x): h = x @ W # regular linear h += x @ W_A @ W_B # low_rank update return scale * h LoRA: Low-Rank Adaptation...
Large language model.MiniGPT-v2 adopts the open-sourced LLaMA2-chat (7B)[50]as the language model backbone. In our work, the language model is treated as a unified interface for various vision-language inputs. We directly rely on the LLaMA-2 language tokens to perform various vision-languag...
(model.config["hidden_size"], class_num) # 将新的分类头添加到模型中 model.cls = cls # 通过微调顶层来适应新任务 for param in model.cls.parameters(): param.trainable = True optimizer = paddle.optimizer.Adam(learning_rate=1e-5, parameters=model.cls.parameters()) criterion = paddle.nn....
Optimizer paged_adamw_32bit paged_adamw_32bitTable 3: Hyper-parameters for LM Generation. Hyper-parameter Value max_length 512 temperature 1.0 top_p 0.9Table 4: Predicted safety margins and empirical confidence intervals for -trained LMs using different dual variables λ. λ 0.10 0.35 0.50 0.75 ...
Large language models (LLMs) have broad medical knowledge and can reason about medical information across many domains, holding promising potential for diverse medical applications in the near future. In this study, we demonstrate a concerning vulnerabil
language may yield less reliable judgements and degrade model competency compared with using model probability scores or training separate classifiers directly from internal representations28,29,30,31. These observations underscore the importance of working with models that are as open as possible, ideally...
As shown in Fig. 2, the core component of PloutsGen pipeline is the diverse expert pool, which is designed to provide signals from a wide range of experts, including sentiment, technical analysis and human analysis, each utilizing a Large Language Model (LLM) to analyze the stock related inf...
Awesome-LLM-Prompt-Optimization: a curated list of advanced prompt optimization and tuning methods in Large Language Models optimizationpromptevolution-strategiesprompt-learningprompt-tuninglarge-language-modelsllmsprompt-optimizationllm-optimizerllm-optimization ...