Beckett Dillon PRO


AI & ML interests

I make music, teach machines, study nature and build things (


Posts 5

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Jamba GGUF!

Finally, thanks to the awesome work of the brilliant mind of Github user compilade ( Jamba is now beginning to be supported in llama.cpp (just CPU inference at the moment). So far there are a few different versions I have been able to convert, mainly the Jamba-Bagel, Jamba-Claude, 900M Jamba-Small and a 1B Jamba

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Craft Your Own Expert LLM - Using 100% Open-Source/Private/Free/Awesome Tools

Hey everyone! After seeing a lot of people's interest in crafting their own datasets and then training their own models, I took it upon myself to try and build a stack to help ease that process. I'm excited to share a major project I've been developing—the Vodalus Expert LLM Forge.

This is a 100% locally LLM-powered tool designed to facilitate high-quality dataset generation. It utilizes free open-source tools so you can keep everything private and within your control.

Why Open Source?

I decided to open source the Vodalus Expert LLM Forge to empower individuals and organizations everywhere to generate their own high-quality data. By making these tools freely available, I hope this community can start crafting their own models with little to no money and/or experience, helping to improve data quality and innovation across the board. While I'm releasing this tool for free, I've also completed an extensive tutorial/course with lots of videos and instructions that guide you through each step of maximizing the potential of this stack. This course is available for purchase at and is designed to enhance your experience and results with the Vodalus Expert LLM Forge.

What’s included in the Vodalus Expert LLM Forge?

- Data Generation: Harness RAG (through AnythingLLM if you are set up properly) and Wikipedia to create datasets via local language models.

- Model Training & Fine-Tuning: Tutorials and Jupyter notebooks to customize models to your specific needs.

- Quantization: Optimize models for performance with our quantization guides.

If this project aids your work, please consider supporting it through a donation at my Your support helps sustain my further LLM developments and experiments, always with a focus on using those efforts to give back to the LLM community.