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99 changes: 73 additions & 26 deletions docs/source/en/model_doc/ernie.md
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Expand Up @@ -14,29 +14,83 @@ rendered properly in your Markdown viewer.

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<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 |
|:-------------------:|:--------:|:-------------------------------:|
Expand All @@ -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

Expand Down Expand Up @@ -116,4 +163,4 @@ and [ERNIE](https://github.com/PaddlePaddle/ERNIE/blob/repro).
## ErnieForQuestionAnswering

[[autodoc]] ErnieForQuestionAnswering
- forward
- forward