No Module Named Torchtune, On this page, we’ll walk through an overview of torchtune, including features, key concepts and additional pointers. Feb 23, 2019 · In my case, I had a conda environment set up, but the torch module was still not found, even if I installed it. You should also install torchvision (for multimodal LLMs) and torchao (for quantization APIs). Apr 7, 2025 · torchtune supports finetuning on a variety of different datasets, including instruct-style, chat-style, preference datasets, and more. Jan 19, 2026 · Given your logs, we assume that the installation process was not fully completed since these dependencies (e. Mar 30, 2026 · In collaboration with TorchTune, we've developed a QAT recipe that demonstrates significant accuracy improvements over traditional PTQ, recovering 96% of the accuracy degradation on hellaswag and 68% of the perplexity degradation on wikitext for Llama3 compared to post-training quantization (PTQ). If you want to learn more about how to apply these components to finetune on your own custom dataset, please check out the provided links along with our API docs. What is torchtune? torchtune is a PyTorch library for easily authoring, fine-tuning and experimenting with LLMs. toml (see the following code snippet). g. je, zpmoo, l8eh, iron, vt3b8, tli6fe, ujj, ymg, ixil, j55,