bert large uncased model

🤗 Huggingface bert-large-uncased

The model bert large uncased is a Natural Language Processing (NLP) Model implemented in Transformer library, generally using the Python programming language.

What is the bert large uncased model?

BERT is a transformers model pretrained on a large corpus of English data in a self-supervised fashion . This model is uncased: it does not make a difference between English and English . It was introduced in a paper and first released in the repository of BERT . The model was pretrained with two objectives: Masked language modeling (MLM) and next sentence prediction (NSP) This way, the model learns an inner representation of the English language that can then be used to extract features that can be used for downstream tasks like sequence classification, token classification or question answering . For tasks such as text-generation you should look at model like GPT2. For tasks,

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Model usage

You can find bert large uncased model easily in transformers python library. To download and use any of the pretrained models on your given task, you just need to use those a few lines of codes (PyTorch version). Here an example to download using pip (a package installer for Python)

Download and install using pip

$ pip install transformers


Usage in python

# Import generic wrappers
from transformers import AutoModel, AutoTokenizer 


# Define the model repo
model_name = "bert-large-uncased" 


# Download pytorch model
model = AutoModel.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)


# Transform input tokens 
inputs = tokenizer("Hello world!", return_tensors="pt")

# Model apply
outputs = model(**inputs)
    

More info about bert-large-uncased

See the paper, download and more info