11/8/2022 0 Comments Google translate speech to text![]() ![]() The easiest way to try out T5 is with a free TPU in our Colab Tutorial.īelow we provide examples for how to pre-train, fine-tune, evaluate, and decode from a model from the command-line with our codebase. Since the HfPyTorchModel is experimental, the remainder of this README assumes usage of the MtfModel and its associated binary.Ī usage example of HfPyTorchModel is available here. If you are interested fine-tuning our models on a GPU in PyTorch, you should try the HfPyTorchModel API. If you want to use our largest models on TPUs and/or reproduce the results in our paper, you should use the MtfModel API and the t5_mesh_transformer binary. The Hugging Face API is currently experimental and subject to change, but provides a simple and easy way to load, fine-tune, and evaluate our pre-trained models using PyTorch on a single GPU. T5.models contains shims for connecting T5 Tasks and Mixtures to a model implementation for training, evaluation, and inference.Ĭurrently there are two shims available: One for the Mesh TensorFlow Transformer that we used in our paper and another for the Hugging Face Transformers library.
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