diff --git a/docs/source/en/model_doc/ernie.md b/docs/source/en/model_doc/ernie.md
index 596a7b1f4b38..8b2290ded685 100644
--- a/docs/source/en/model_doc/ernie.md
+++ b/docs/source/en/model_doc/ernie.md
@@ -14,29 +14,83 @@ rendered properly in your Markdown viewer.
 
 -->
 
+<div style="float: right;">
+    <div class="flex flex-wrap space-x-1">
+        <img alt="PyTorch" src="https://img.shields.io/badge/PyTorch-DE3412?style=flat&logo=pytorch&logoColor=white" >
+    </div>
+</div>
+
 # ERNIE
 
-<div class="flex flex-wrap space-x-1">
-<img alt="PyTorch" src="https://img.shields.io/badge/PyTorch-DE3412?style=flat&logo=pytorch&logoColor=white">
-</div>
+[ERNIE1.0](https://arxiv.org/abs/1904.09223), [ERNIE2.0](https://ojs.aaai.org/index.php/AAAI/article/view/6428),
+[ERNIE3.0](https://arxiv.org/abs/2107.02137), [ERNIE-Gram](https://arxiv.org/abs/2010.12148), [ERNIE-health](https://arxiv.org/abs/2110.07244) are a series of powerful models proposed by baidu, especially in Chinese tasks.
+
+ERNIE (Enhanced Representation through kNowledge IntEgration) is designed to learn language representation enhanced by knowledge masking strategies, which includes entity-level masking and phrase-level masking.
+
+Other ERNIE models released by baidu can be found at [Ernie 4.5](./ernie4_5.md), and [Ernie 4.5 MoE](./ernie4_5_moe.md).
+
+> [!TIP]
+> This model was contributed by [nghuyong](https://huggingface.co/nghuyong), and the official code can be found in [PaddleNLP](https://github.com/PaddlePaddle/PaddleNLP) (in PaddlePaddle).
+>
+> Click on the ERNIE models in the right sidebar for more examples of how to apply ERNIE to different language tasks.
+
+The example below demonstrates how to predict the `[MASK]` token with [`Pipeline`], [`AutoModel`], and from the command line.
 
-## Overview
-ERNIE is a series of powerful models proposed by baidu, especially in Chinese tasks,
-including [ERNIE1.0](https://huggingface.co/papers/1904.09223), [ERNIE2.0](https://ojs.aaai.org/index.php/AAAI/article/view/6428),
-[ERNIE3.0](https://huggingface.co/papers/2107.02137), [ERNIE-Gram](https://huggingface.co/papers/2010.12148), [ERNIE-health](https://huggingface.co/papers/2110.07244), etc.
+<hfoptions id="usage">
+<hfoption id="Pipeline">
 
-These models are contributed by [nghuyong](https://huggingface.co/nghuyong) and the official code can be found in [PaddleNLP](https://github.com/PaddlePaddle/PaddleNLP) (in PaddlePaddle).
+```py
+from transformers import pipeline
 
-### Usage example
-Take `ernie-1.0-base-zh` as an example:
+pipeline = pipeline(
+    task="fill-mask",
+    model="nghuyong/ernie-3.0-xbase-zh"
+)
 
-```Python
-from transformers import AutoTokenizer, AutoModel
-tokenizer = AutoTokenizer.from_pretrained("nghuyong/ernie-1.0-base-zh")
-model = AutoModel.from_pretrained("nghuyong/ernie-1.0-base-zh")
+pipeline("巴黎是[MASK]国的首都。")
 ```
 
-### Model checkpoints
+</hfoption>
+<hfoption id="AutoModel">
+
+```py
+import torch
+from transformers import AutoModelForMaskedLM, AutoTokenizer
+
+tokenizer = AutoTokenizer.from_pretrained(
+    "nghuyong/ernie-3.0-xbase-zh",
+)
+model = AutoModelForMaskedLM.from_pretrained(
+    "nghuyong/ernie-3.0-xbase-zh",
+    torch_dtype=torch.float16,
+    device_map="auto"
+)
+inputs = tokenizer("巴黎是[MASK]国的首都。", return_tensors="pt").to("cuda")
+
+with torch.no_grad():
+    outputs = model(**inputs)
+    predictions = outputs.logits
+
+masked_index = torch.where(inputs['input_ids'] == tokenizer.mask_token_id)[1]
+predicted_token_id = predictions[0, masked_index].argmax(dim=-1)
+predicted_token = tokenizer.decode(predicted_token_id)
+
+print(f"The predicted token is: {predicted_token}")
+```
+
+</hfoption>
+<hfoption id="transformers CLI">
+
+```bash
+echo -e "巴黎是[MASK]国的首都。" | transformers run --task fill-mask --model nghuyong/ernie-3.0-xbase-zh --device 0
+```
+
+</hfoption>
+</hfoptions>
+
+## Notes
+
+Model variants are available in different sizes and languages.
 
 |     Model Name      | Language |           Description           |
 |:-------------------:|:--------:|:-------------------------------:|
@@ -51,18 +105,11 @@ model = AutoModel.from_pretrained("nghuyong/ernie-1.0-base-zh")
 |   ernie-health-zh   | Chinese  | Layer:12, Heads:12, Hidden:768  |
 |    ernie-gram-zh    | Chinese  | Layer:12, Heads:12, Hidden:768  |
 
-You can find all the supported models from huggingface's model hub: [huggingface.co/nghuyong](https://huggingface.co/nghuyong), and model details from paddle's official
-repo: [PaddleNLP](https://paddlenlp.readthedocs.io/zh/latest/model_zoo/transformers/ERNIE/contents.html)
-and [ERNIE](https://github.com/PaddlePaddle/ERNIE/blob/repro).
-
 ## Resources
 
-- [Text classification task guide](../tasks/sequence_classification)
-- [Token classification task guide](../tasks/token_classification)
-- [Question answering task guide](../tasks/question_answering)
-- [Causal language modeling task guide](../tasks/language_modeling)
-- [Masked language modeling task guide](../tasks/masked_language_modeling)
-- [Multiple choice task guide](../tasks/multiple_choice)
+You can find all the supported models from huggingface's model hub: [huggingface.co/nghuyong](https://huggingface.co/nghuyong), and model details from paddle's official
+repo: [PaddleNLP](https://paddlenlp.readthedocs.io/zh/latest/model_zoo/transformers/ERNIE/contents.html)
+and [ERNIE's legacy branch](https://github.com/PaddlePaddle/ERNIE/tree/legacy/develop).
 
 ## ErnieConfig
 
@@ -116,4 +163,4 @@ and [ERNIE](https://github.com/PaddlePaddle/ERNIE/blob/repro).
 ## ErnieForQuestionAnswering
 
 [[autodoc]] ErnieForQuestionAnswering
-    - forward
\ No newline at end of file
+    - forward