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Commit 83076c16 authored by Hongkun Yu's avatar Hongkun Yu Committed by A. Unique TensorFlower
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Fix bert readme. Always use keras_bert path. 

PiperOrigin-RevId: 286327318
parent 1722b691
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official/nlp/bert/README.md
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......@@ -141,7 +141,7 @@ and unpack it to some directory `$GLUE_DIR`.
```shell
export GLUE_DIR=~/glue
export BERT_BASE_DIR=gs://cloud-tpu-checkpoints/bert/tf_20/uncased_L-24_H-1024_A-16
export BERT_BASE_DIR=gs://cloud-tpu-checkpoints/bert/keras_bert/uncased_L-24_H-1024_A-16
export TASK_NAME=MNLI
export OUTPUT_DIR=gs://some_bucket/datasets
......@@ -172,7 +172,7 @@ The necessary files can be found here:
```shell
export SQUAD_DIR=~/squad
export SQUAD_VERSION=v1.1
export BERT_BASE_DIR=gs://cloud-tpu-checkpoints/bert/tf_20/uncased_L-24_H-1024_A-16
export BERT_BASE_DIR=gs://cloud-tpu-checkpoints/bert/keras_bert/uncased_L-24_H-1024_A-16
export OUTPUT_DIR=gs://some_bucket/datasets
python create_finetuning_data.py \
......@@ -190,7 +190,7 @@ python create_finetuning_data.py \
* Cloud Storage
The unzipped pre-trained model files can also be found in the Google Cloud
Storage folder `gs://cloud-tpu-checkpoints/bert/tf_20`. For example:
Storage folder `gs://cloud-tpu-checkpoints/bert/keras_bert`. For example:
```shell
export BERT_BASE_DIR=gs://cloud-tpu-checkpoints/bert/keras_bert/uncased_L-24_H-1024_A-16
......@@ -221,7 +221,7 @@ For GPU memory of 16GB or smaller, you may try to use `BERT-Base`
(uncased_L-12_H-768_A-12).
```shell
export BERT_BASE_DIR=gs://cloud-tpu-checkpoints/bert/tf_20/uncased_L-24_H-1024_A-16
export BERT_BASE_DIR=gs://cloud-tpu-checkpoints/bert/keras_bert/uncased_L-24_H-1024_A-16
export MODEL_DIR=gs://some_bucket/my_output_dir
export GLUE_DIR=gs://some_bucket/datasets
export TASK=MRPC
......@@ -246,7 +246,7 @@ To use TPU, you only need to switch distribution strategy type to `tpu` with TPU
information and use remote storage for model checkpoints.
```shell
export BERT_BASE_DIR=gs://cloud-tpu-checkpoints/bert/tf_20/uncased_L-24_H-1024_A-16
export BERT_BASE_DIR=gs://cloud-tpu-checkpoints/bert/keras_bert/uncased_L-24_H-1024_A-16
export TPU_IP_ADDRESS='???'
export MODEL_DIR=gs://some_bucket/my_output_dir
export GLUE_DIR=gs://some_bucket/datasets
......@@ -278,7 +278,7 @@ For GPU memory of 16GB or smaller, you may try to use `BERT-Base`
(uncased_L-12_H-768_A-12).
```shell
export BERT_BASE_DIR=gs://cloud-tpu-checkpoints/bert/tf_20/uncased_L-24_H-1024_A-16
export BERT_BASE_DIR=gs://cloud-tpu-checkpoints/bert/keras_bert/uncased_L-24_H-1024_A-16
export SQUAD_DIR=gs://some_bucket/datasets
export MODEL_DIR=gs://some_bucket/my_output_dir
export SQUAD_VERSION=v1.1
......@@ -302,7 +302,7 @@ To use TPU, you need switch distribution strategy type to `tpu` with TPU
information.
```shell
export BERT_BASE_DIR=gs://cloud-tpu-checkpoints/bert/tf_20/uncased_L-24_H-1024_A-16
export BERT_BASE_DIR=gs://cloud-tpu-checkpoints/bert/keras_bert/uncased_L-24_H-1024_A-16
export TPU_IP_ADDRESS='???'
export MODEL_DIR=gs://some_bucket/my_output_dir
export SQUAD_DIR=gs://some_bucket/datasets
......
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