distilbert base uncased model

🤗 Huggingface distilbert-base-uncased

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

What is the distilbert base uncased model?

DistilBERT is a transformers model, smaller and faster than BERT, which was pretrained on the same corpus in a self-supervised fashion, using the BERT base model as a teacher . This model is uncased: it does not make a difference between English and English . The model is primarily aimed at being fine-tuned on tasks that use the whole sentence (potentially masked) to make decisions, such as sequence classification, token classification or question answering . For tasks such as text-generation you should look at model like GPT2. For tasks like text-language-generation, you should . use the raw model for either masked language modeling or next sentence,

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Model usage

You can find distilbert 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 = "distilbert-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 distilbert-base-uncased

See the paper, download and more info