Category/Tag: Tutorials
AI Tutorial: Hybrid Search in Detail
- By Bruce Nielson
- ML & AI Specialist
In a previous post, we talked about how AI developers can combine lexical and semantic search results to create a better answer/response. Today, in this article by Bruce Nielson, we'll look a bit deeper into how you can make your AI search tools far more intelligent.
A Local Text-to-Speech Model Using Suno Bark
- By Bruce Nielson
- ML & AI Specialist
In our last post, we looked at how to stream a text-to-speech model using the Hugging Face API. We had mixed results at best. So, in this post, we'll be covering how to do text-to-speech (TTS) using a local TTS model with the help of Suno Bark and Hugging Face.
Testing Hugging Face Serverless Text-To-Speech Models
- By Bruce Nielson
- ML & AI Specialist
Looking to make your AI a bit more personable or easier to communicate with? In today's article by Bruce Nielson, we'll be testing out some ways of making an LLM have text-to-speech functionality using the Hugging Face framework.
PDFs vs HTML: The Importance of Metadata for Retrieval Augmented Generation
- By Bruce Nielson
- ML & AI Specialist
In our ongoing series of AI tutorials, we have been focusing on using EBUP documents instead of PDFs. In today's article, we will dive a bit into the reasons for why that is, and the differences between PDFs and HTML documents when it comes to AI frameworks. We also have a look into how you can use PDF documents with AI.
Implementing a Lexical Search
- By Bruce Nielson
- ML & AI Specialist
In a previous post, our expert on AI, Bruce Nielson, discussed how to run a hybrid search using AI wherein we could merge a lexical search and a semantic search together to create single higher quality result. Today, we will dive into how to conduct just a lexical search as to better showcase the differences.
Hybrid Search for Retrieval Augmented Generation
- By Bruce Nielson
- ML & AI Specialist
In a previous blog post, we introduced our "Book Search Archive," which we have been using to experiment with using AI to search and extrapolate information. In today's blog post with Bruce Nielson, we'll be discussing "hybrid searches" to better improve upon our AI model and showcase the power of an AI-driven search.
An AI Tech Support Agent
- By Bruce Nielson
- ML & AI Specialist
Large companies love to talk about AI and how they are trying to incorporate it into their business model. However, especially for smaller companies, some business owners may assume that there just isn't any real use for AI in their industry, causing them to feel like they are falling behind everyone else in modernizing their company. In today's article by Bruce Nielson, we'll dive into one real-world example of how any business can take advantage of AI: An AI Tech Support Agent.
Haystack Streaming Text Generation
- By Bruce Nielson
- ML & AI Specialist
In this post, we're going to give our sample Retrieval Augmented Generation (RAG) Pipeline a bit of a makeover. Specifically, we’ll tweak it to “stream” results from multiple nodes, letting us show off what we’ve got as soon as it rolls in—no more waiting for everything to pile up at the end.
Avoiding Text Truncations in RAG
- By Bruce Nielson
- ML & AI Specialist
In our series of articles on AI, we have been exploring cost-effective ways of building AI and ML models ourselves, helping anyone get into AI right now. However, a downside of the sentence embedder model we have been using is a tendency for text to get truncated, reducing overall performance of the RAG system. In today's article, we will explore how to overcome that problem.
Using Hugging Face API Generators for RAG
- By Bruce Nielson
- ML & AI Specialist
Want to take advantage of AI and ML, but don't want to break the bank while doing so? Mindfire TECH is eager to help you and your business enter the future. Part of that includes our ongoing free series of tutorials and demos showcasing how you can get started with AI and ML right now. In this one, join Bruce Nielson as he explored how to use Hugging Face Generators for RAG.