06f1fd69a6
5.2 KiB
This model was published in HF papers on 2019-04-19 and contributed to Hugging Face Transformers on 2022-09-09.
ERNIE
ERNIE1.0, ERNIE2.0, ERNIE3.0, ERNIE-Gram, ERNIE-health 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, and Ernie 4.5 MoE.
Tip
This model was contributed by nghuyong, and the official code can be found in 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.
from transformers import pipeline
pipeline = pipeline(
task="fill-mask",
model="nghuyong/ernie-3.0-xbase-zh"
)
pipeline("巴黎是[MASK]国的首都。")
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",
device_map="auto"
)
inputs = tokenizer("巴黎是[MASK]国的首都。", return_tensors="pt").to(model.device)
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}")
Notes
Model variants are available in different sizes and languages.
| Model Name | Language | Description |
|---|---|---|
| ernie-1.0-base-zh | Chinese | Layer:12, Heads:12, Hidden:768 |
| ernie-2.0-base-en | English | Layer:12, Heads:12, Hidden:768 |
| ernie-2.0-large-en | English | Layer:24, Heads:16, Hidden:1024 |
| ernie-3.0-base-zh | Chinese | Layer:12, Heads:12, Hidden:768 |
| ernie-3.0-medium-zh | Chinese | Layer:6, Heads:12, Hidden:768 |
| ernie-3.0-mini-zh | Chinese | Layer:6, Heads:12, Hidden:384 |
| ernie-3.0-micro-zh | Chinese | Layer:4, Heads:12, Hidden:384 |
| ernie-3.0-nano-zh | Chinese | Layer:4, Heads:12, Hidden:312 |
| ernie-health-zh | Chinese | Layer:12, Heads:12, Hidden:768 |
| ernie-gram-zh | Chinese | Layer:12, Heads:12, Hidden:768 |
Resources
You can find all the supported models from huggingface's model hub: huggingface.co/nghuyong, and model details from paddle's official repo: PaddleNLP and ERNIE's legacy branch.
ErnieConfig
autodoc ErnieConfig - all
Ernie specific outputs
autodoc models.ernie.modeling_ernie.ErnieForPreTrainingOutput
ErnieModel
autodoc ErnieModel - forward
ErnieForPreTraining
autodoc ErnieForPreTraining - forward
ErnieForCausalLM
autodoc ErnieForCausalLM - forward
ErnieForMaskedLM
autodoc ErnieForMaskedLM - forward
ErnieForNextSentencePrediction
autodoc ErnieForNextSentencePrediction - forward
ErnieForSequenceClassification
autodoc ErnieForSequenceClassification - forward
ErnieForMultipleChoice
autodoc ErnieForMultipleChoice - forward
ErnieForTokenClassification
autodoc ErnieForTokenClassification - forward
ErnieForQuestionAnswering
autodoc ErnieForQuestionAnswering - forward