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bert base cased model

🤗 Huggingface bert-base-cased

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

What is the bert base cased model?

BERT is a transformers model pretrained on a large corpus of English data in a self-supervised fashion . This model is case-sensitive: it makes a difference between English and English . It's mostly intended to be fine-tuned on downstream tasks that use the whole sentence (potentially masked)to make decisions, such as sequence classification, token classification or question answering . The team releasing BERT did not write a model card for this model so this model card has been written by the Hugging Face team . It was introduced in a paper and first released in the PePean repository . The model was pretrained with two objectives: Masked language modeling (MLM),

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Model usage

You can find bert base cased 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-base-cased" 


# 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-base-cased

See the paper, download and more info


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