voxtir VS modelfusion

A simple service intended for transcribing interviews and allowing for easy export to word. Turns out it works quite well for fine-tuning speech to text models. Hosted on AWS using founder credits. Uses whisper and Pyannote.

Code for fine-tuning can be found here https://github.com/Voxtir/whisper-fine-tuning-voxtir

and general source code found here https://github.com/Voxtir/voxtir/issues

Rolling it out to students and journalists. Feel free to reach out if you want to discuss it, contribute, or something else.

ModelFusion is an AI integration library that I am developing. It enables you to integrate AI models into your JavaScript and TypeScript applications. You can install it with the following command:

ModelFusion is an open-source library I'm developing to integrate AI models seamlessly into TypeScript projects. It provides an Ollama client and a generateStructure function.

ModelFusion: ModelFusion is a library for building multi-modal AI applications that I've been working on. It provides a streamText function that calls AI models and returns a streaming response. ModelFusion also contains an Ollama integration that we will use to access the OpenHermes 2.5 Mistral model.

You can find the complete code for the chatbot here: github/com/lgrammel/modelfusion/examples/pdf-chat-terminal

I’m working on ModelFusion, a TypeScript library for working with AI models (llm, image, etc.)

https://github.com/lgrammel/modelfusion

It is only getting limited traction so I’m wondering if I’m missing something fundamental with the approach that I’m taking.

If you work with JS or TS, check out this alternative that I've been working on:

https://github.com/lgrammel/modelfusion

It lets you stay in full control over the prompts and control flow while make a lot of things easier and more convenient.

The response also contains additional information such as the metadata and the full response. The ModelFusion documentation contains many examples and demo apps.