PyLitSense: An easy way to try biomedical sentence embeddings
Retrieval augmented generation can ground large language models to improve their response accuracy, recency, and referenceability. This can be particularly i...
Recent Posts
Introducing Agentflow: Execute complex LLM workflows with simple JSON
Large language models (LLMs) are powerful tools, but implementing complex workflows with them can be a challenge.
Use OpenAI API streaming with functions
The OpenAI API provides offers several features to facilitate using powerful language models like GPT-4 and GPT 3.5.
Fine-tune T5 with Hugging Face (as of September 9, 2022)
Hugging Face is a great resource for streamlining the use of machine learning in applications. It can be challenging, however, to know what documentation and...
Use offset to work with unindexed arrays in BigQuery
Recently I faced a challenge of working with multilevel nested arrays in BigQuery. The table I was working with had a structure somewhat like this:
Extract structured data from unstructured text using language models like GPT-3
Recently I faced a common challenge: extracting structured information from millions of unstructured text documents.
Get colors from images as swatches
A few weeks ago I was playing with scientific figures and wondering how I might extract insights from them. One idea I had was to find all the colors in scie...
Extract table data from images with pure Pytesseract
When extracting data from documents, one common challenge is processing text in images. This can be particularly difficult when the text is in tables. You do...