The exaggeration here is almost comical: "We're excited to introduce SmolLM, a series of *state-of-the-art* small language models available in three sizes: 135M, 360M, and 1.7B parameters." State-of-the-art! It’s disappointing to see so much time, money, and energy poured into this with so little to show for it—especially considering the environmental impact, with carbon emissions soaring. While I can appreciate the effort, the process is far from flawless. Even the dataset, "SmolLM-Corpus," leaves much to be desired; when I randomly examined some samples from the dataset, the quality was shockingly poor. It’s puzzling—why can't all the resources Hugging Face has access to translate into more substantial results? Theoretically, with the resources Hugging Face has, it should be possible to create a 135M model that performs far better than what we currently see.