From 31838d3e11c6214df8f7c4427d6524ae9328eed0 Mon Sep 17 00:00:00 2001 From: Stas Bekman Date: Mon, 10 Jan 2022 08:44:33 -0800 Subject: [PATCH] [doc] normalize HF Transformers string (#15023) --- docs/source/benchmarks.mdx | 8 ++++---- docs/source/testing.mdx | 2 +- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/docs/source/benchmarks.mdx b/docs/source/benchmarks.mdx index 8752f76305..7182e4d39f 100644 --- a/docs/source/benchmarks.mdx +++ b/docs/source/benchmarks.mdx @@ -14,13 +14,13 @@ specific language governing permissions and limitations under the License. [[open-in-colab]] -Let's take a look at how 🤗 Transformer models can be benchmarked, best practices, and already available benchmarks. +Let's take a look at how 🤗 Transformers models can be benchmarked, best practices, and already available benchmarks. -A notebook explaining in more detail how to benchmark 🤗 Transformer models can be found [here](https://github.com/huggingface/notebooks/tree/master/examples/benchmark.ipynb). +A notebook explaining in more detail how to benchmark 🤗 Transformers models can be found [here](https://github.com/huggingface/notebooks/tree/master/examples/benchmark.ipynb). -## How to benchmark 🤗 Transformer models +## How to benchmark 🤗 Transformers models -The classes [`PyTorchBenchmark`] and [`TensorFlowBenchmark`] allow to flexibly benchmark 🤗 Transformer models. The benchmark classes allow us to measure the _peak memory usage_ and _required time_ for both _inference_ and _training_. +The classes [`PyTorchBenchmark`] and [`TensorFlowBenchmark`] allow to flexibly benchmark 🤗 Transformers models. The benchmark classes allow us to measure the _peak memory usage_ and _required time_ for both _inference_ and _training_. diff --git a/docs/source/testing.mdx b/docs/source/testing.mdx index 7e908f156d..fa4bf298d5 100644 --- a/docs/source/testing.mdx +++ b/docs/source/testing.mdx @@ -13,7 +13,7 @@ specific language governing permissions and limitations under the License. # Testing -Let's take a look at how 🤗 Transformer models are tested and how you can write new tests and improve the existing ones. +Let's take a look at how 🤗 Transformers models are tested and how you can write new tests and improve the existing ones. There are 2 test suites in the repository: