Bart Base Portuguese

🚀 BART (Base-sized Model)

BART is a Portuguese pre-trained model. It addresses the need for natural language processing tasks in Portuguese, offering capabilities for text generation and comprehension.

🚀 Quick Start

✨ Features

BART is a transformer encoder-decoder (seq2seq) model. It has a bidirectional encoder (similar to BERT) and an autoregressive decoder (similar to GPT). BART is pre-trained by (1) corrupting the text with an arbitrary noise function and (2) learning a model to reconstruct the original text.

BART is particularly effective when fine-tuned for text generation (e.g., summarization, translation), but it also performs well on comprehension tasks (e.g., text classification and QA).

📦 Installation

No specific installation steps provided in the original README.

💻 Usage Examples

Basic Usage

from transformers import BartTokenizer, BartModel

tokenizer = BartTokenizer.from_pretrained('adalbertojunior/bart-base-portuguese')
model = BartModel.from_pretrained('adalbertojunior/bart-base-portuguese')

inputs = tokenizer("No meio do caminho havia uma pedra", return_tensors="pt")
outputs = model(**inputs)

last_hidden_states = outputs.last_hidden_state

📚 Documentation

You can use the base model for text filling. However, the model will be more useful after fine-tuning on a dataset for a specific task.

📄 License

No license information provided in the original README.

BibTeX Citation

@misc {adalberto_ferreira_barbosa_junior_2024,
	author       = { {Adalberto Ferreira Barbosa Junior} },
	title        = { bart-base-portuguese (Revision 149de72) },
	year         = 2024,
	url          = { https://huggingface.co/adalbertojunior/bart-base-portuguese },
	doi          = { 10.57967/hf/3264 },
	publisher    = { Hugging Face }
}

Information Table