llms

905 bookmarks · page 12 of 19
2024-06-30 · marktechpost.com

A Comprehensive Overview of Prompt Engineering for ChatGPT

Prompt engineering is crucial to leveraging ChatGPT's capabilities, enabling users to elicit relevant, accurate, high-quality responses from the model. As language models like ChatGPT become more sophisticated, mastering the art of crafting effective prompts has become…

2024-06-20 · marktechpost.com

Key Metrics for Evaluating Large Language Models (LLMs)

Evaluating Large Language Models (LLMs) is a challenging problem in language modeling, as real-world problems are complex and variable. Conventional benchmarks frequently fail to fully represent LLMs' all-encompassing performance. A recent LinkedIn post has emphasized a number…

2024-06-19 · m.youtube.com

Let's reproduce GPT-2 (124M)

We reproduce the GPT-2 (124M) from scratch. This video covers the whole process: First we build the GPT-2 network, then we optimize its training to be really fast, then we set up the training run following the GPT-2 and GPT-3 paper and their hyperparameters, then we hit run, and…

2024-05-11 · docs.unstructured.io

Cleaning

As part of data preparation for an NLP model, it’s common to need to clean up your data prior to passing it into the model. If there’s unwanted content in your output, for example, it could impact the quality of your NLP model. To help with this, the `unstructured` library…

2024-05-05 · huggingface.co

Hugging Face - Documentation

We’re on a journey to advance and democratize artificial intelligence through open source and open science.