Updates the default branch from master to main (#16326)
* Updates the default branch from master to main * Links from `master` to `main` * Typo * Update examples/flax/README.md Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
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@@ -1761,7 +1761,7 @@ In your report please always include:
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5. Unless it's impossible please always use a standard dataset that we can use and not something custom.
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6. If possible try to use one of the existing [examples](https://github.com/huggingface/transformers/tree/master/examples/pytorch) to reproduce the problem with.
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6. If possible try to use one of the existing [examples](https://github.com/huggingface/transformers/tree/main/examples/pytorch) to reproduce the problem with.
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Things to consider:
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@@ -1985,7 +1985,7 @@ train_batch_size = 1 * world_size
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# - which params should remain on gpus - the larger the value the smaller the offload size
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#
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# For indepth info on Deepspeed config see
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# https://huggingface.co/docs/transformers/master/main_classes/deepspeed
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# https://huggingface.co/docs/transformers/main/main_classes/deepspeed
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# keeping the same format as json for consistency, except it uses lower case for true/false
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# fmt: off
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@@ -82,7 +82,7 @@ This library hosts the processor to load the XNLI data:
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Please note that since the gold labels are available on the test set, evaluation is performed on the test set.
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An example using these processors is given in the [run_xnli.py](https://github.com/huggingface/transformers/tree/master/examples/legacy/text-classification/run_xnli.py) script.
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An example using these processors is given in the [run_xnli.py](https://github.com/huggingface/transformers/tree/main/examples/legacy/text-classification/run_xnli.py) script.
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## SQuAD
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@@ -156,4 +156,4 @@ features = squad_convert_examples_to_features(
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)
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```
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Another example using these processors is given in the [run_squad.py](https://github.com/huggingface/transformers/tree/master/examples/legacy/question-answering/run_squad.py) script.
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Another example using these processors is given in the [run_squad.py](https://github.com/huggingface/transformers/tree/main/examples/legacy/question-answering/run_squad.py) script.
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