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Translation using the SalamandraTA 2B model
Neuralmind Bert Base Portuguese Cased is a Portuguese language model based on the BERT (Bidirectional Encoder Representations from Transformers) architecture. It is specifically designed to handle text generation and language understanding tasks in Portuguese, making it suitable for applications like language translation, text summarization, and conversational systems. This model is cased, meaning it is sensitive to uppercase and lowercase letters, which can be important for preserving context and meaning in certain tasks.
pip install transformers
from transformers import pipeline
generator = pipeline('text-generation', model='neuralmind/bert-base-portuguese-cased')
tokenizer = AutoTokenizer.from_pretrained('neuralmind/bert-base-portuguese-cased')
model = AutoModelForCausalLM.from_pretrained('neuralmind/bert-base-portuguese-cased')
text = "Escreva um resumo sobre inteligência artificial."
output = generator(text, max_length=100)
print(output[0]['text'])
What tasks is Neuralmind Bert Base Portuguese Cased best suited for?
Neuralmind Bert Base Portuguese Cased is ideal for text generation, translation, summarization, and conversational applications in Portuguese. It excels in understanding and producing contextually accurate text.
How does the cased version differ from the uncased version?
The cased version retains case sensitivity, which is important for distinguishing between proper nouns, acronyms, and specific terms. The uncased version normalizes all text to lowercase, which can be less effective in preserving context.
Can this model handle Brazilian Portuguese?
Yes, Neuralmind Bert Base Portuguese Cased is trained on data that includes both European and Brazilian Portuguese, making it versatile for different regional variations of the language.