Which LLM to choose for your use case?
Given the number of Large Language Models (LLMs) out there, finding one that meets your specific use case can be a daunting task. The field is evolving rapidly, with new models and fine-tuned versions being released every single week. It follows that any list of LLMs and how they should be applied will be rapidly […]
Implementing RAG for your LLM (Mistral)
Most of the open-source models available on Huggingface come pre-trained on a large corpus of publicly available data, like WebText. In general, the size of these datasets give large language models (LLMs) an adequate performance for various use cases. For some, more specific, use cases, however, more domain specific knowledge is required for the LLM […]
Falcon LLM fine-tuning
In the good old days machine learning models were made from scratch by data scientists. This involved acquiring, and cleaning data before training a model and getting it to production. In recent years, though, the size of models has increased, and thus the training data required to train these new larger models as well. This […]