Source:How to Train Long-Context Language Models (Effectively) Code:ProLong HF Page:princeton-nlp/prolong 摘要 本文研究了Language Model的继续预训练和监督微调(SFT),以有效利用长上下文信息。本文首先建立了一个可靠的评估协议来指导模型开发——本文使用了一组广泛的长上下文任务,而不是困惑度或简单的大海捞针...
New research from DeepMind attempts to investigate the optimal model size and the number of tokens for training a transformer language model under a given compute budget.
I am new to LLMs and trying to figure out how to train the model with a bunch of files. I want to train the model with my files (living in a folder on my laptop) and then be able to use the model to ask questions and get answers. With OpenAI, folks have suggested using their...
The prompt is one of the best ways you can influence the outcome of the LLM, and in this article, we’ll share some tips and tricks on how to get your prompts right. Prompts 101 It’s quite expensive to build and train your own Large Language Models. Most people prefer to use a pr...
In this work, we test the limits of improving foundation model performance without continual updating through an initial study of knowledge transfer using either existing intra- and inter- domain benchmarks or explanations generated from large language models (LLMs). We evaluate on 12 public bench...
Maybefine-tune the model (train it some more). Now, this is a great approach, but if we only ever do this, we lack the understanding behind creating our own transformers models. And, if we cannot create our own transformer models — we must rely on there being a pre-trained model tha...
Large language models such as ChatGPT arguably pass the Turing test, meaning they are indistinguishable from people in conversation. But whereas humans grasp whole sentences, LLMs mostly work by predicting one word at a time. Now researchers from Hong Kong Polytechnic University have tested if a ...
Why Is It Important to Estimate the Time and Cost to Train Machine Learning Models? It is of utmost importance to make an accurate estimation of the time and cost required to train a machine learning model. This is especially true when you are training your model on a massive ...
The traditional methodto train LLMs for reasoning tasks is supervised fine-tuning. The engineering team must gather a set of CoT examples to fine-tune the LLM. The examples can be created manually or with the help of a strong LLM likeGPT-4. ...
Trained for Specific Tasks:The Jack-of-all-trade tools that are the public face of LLMs are prone to errors. But as they develop and users train them for specific needs, LLMs can play a large role in fields like medicine, law, finance, and education. ...