bert base uncased model

🤗 Huggingface bert-base-uncased

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

What is the bert base uncased model?

BERT is a self-supervised model on English language using a masked language modeling (MLM) objective . This model is uncased: it does not make 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 . For tasks such as text-generation you should look at model like GPT2. For example, the model was pretrained on the raw texts only, with no,

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Model usage

You can find bert base 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-base-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-base-uncased

See the paper, download and more info