What if I want to serve a Huggingface model on ClearML? Where do I start? In general, machine learning engineers know by now that a good model serving engine is invaluable when serving models in production. These days, NVIDIA’s Triton inference engine is a popular option to do so, but it is lacking in some respects.
Like humans, Machine Learning (ML) models can recognize intricate patterns and anticipate the outcome of new data. On some natural language problems, ML models have even surpassed human performance. But much like people, ML models are susceptible to error. For every ML application in the real world, estimating how frequently a model will be inaccurate is essential. Intuitively presenting information and emphasizing the best ways to enhance a model are equally important.