Watsonx.ai is IBM’s enterprise studio for AI builders to train, validate, tune and deploy Large Language Models. It comes with multiple open source and IBM LLMs which can be accessed via REST API. ...

Via quantization LLMs can run faster and on smaller hardware. This post describes how to run Mistral 7b on an older MacBook Pro without GPU. Llama.cpp is an inference stack implemented in C/C++ to...

Fine-tuning and aligning language models to follow instructions requires high quality data and a large quantity of data. IBM published a paper that describes how synthetic data can be generated wit...

Larger Large Language Models like ChatGPT can be prompted to behave as agents for specific use cases. They can return output in certain formats, and they can return instructions to invoke code. Thi...

With the Text Generation Inference toolkit from Hugging Face Large Language Models can be hosted efficiently. This post describes how to run open-source models or fine-tuned models on IBM Cloud. T...

What a great year 2023 has been! When ChatGPT was published at the end of 2022, I knew it would change the world. I wanted to learn and understand this technology. Fortunately, through my network ...

After Large Language Models have been fine-tuned, the quality needs to be evaluated. This post describes a simple s example utilizing a custom evaluation mechanism. For standard LLM tasks there ar...

Smaller and/or quanitzed Large Language Models can be fine-tuned on a single GPU. For example for FLAN T5 XL (3b) a Nvidia V100 GPU with 16GB is sufficient. This post demonstrates a simple example ...

Before the actual fine-tuning of Large Language Models can start, data needs to be prepared and the code needs to be checked whether it works. This post describes how to do this efficiently locally...

Fine-tuning Large Language Models requires GPUs. When tuning small and/or quantized models, single GPUs can be sufficient. This post explains how to leverage a Nvidia V100 GPU in the IBM Cloud. Ov...