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Fix broken links (#39809)

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Replace links in the form of `[text]((url))` to `[text](url)`. This is
the correct format of a url in the markdown.
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Tommy Chiang
2025-07-31 21:23:04 +08:00
committed by GitHub
parent b937d47455
commit 4fcf455517
10 changed files with 11 additions and 11 deletions
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docs/source/en/serialization.md
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@@ -18,7 +18,7 @@ rendered properly in your Markdown viewer.
[ONNX](http://onnx.ai) is an open standard that defines a common set of operators and a file format to represent deep learning models in different frameworks, including PyTorch and TensorFlow. When a model is exported to ONNX, the operators construct a computational graph (or *intermediate representation*) which represents the flow of data through the model. Standardized operators and data types makes it easy to switch between frameworks.
The [Optimum](https://huggingface.co/docs/optimum/index) library exports a model to ONNX with configuration objects which are supported for [many architectures]((https://huggingface.co/docs/optimum/exporters/onnx/overview)) and can be easily extended. If a model isn't supported, feel free to make a [contribution](https://huggingface.co/docs/optimum/exporters/onnx/usage_guides/contribute) to Optimum.
The [Optimum](https://huggingface.co/docs/optimum/index) library exports a model to ONNX with configuration objects which are supported for [many architectures](https://huggingface.co/docs/optimum/exporters/onnx/overview) and can be easily extended. If a model isn't supported, feel free to make a [contribution](https://huggingface.co/docs/optimum/exporters/onnx/usage_guides/contribute) to Optimum.
The benefits of exporting to ONNX include the following.