Agriculture Bert Base Chinese

🚀 agriculture-bert-base-chinese

This is a BERT model designed for the agriculture domain, trained using the Masked Language Modeling (MLM) self - supervised learning approach.

🚀 Quick Start

This BERT model is specifically tailored for the agriculture domain. It leverages the self - supervised learning method of Masked Language Modeling (MLM) for training.

• Masked language modeling (MLM): Given a sentence, the model randomly masks 15% of the words in the input. Then, it processes the entire masked sentence through the model and predicts the masked words.
• This differs from traditional recurrent neural networks (RNNs) that typically process words sequentially, and from autoregressive models like GPT which internally mask future tokens.
• It enables the model to learn a bidirectional representation of the sentence.

💻 Usage Examples

Basic Usage

from transformers import pipeline
fill_mask = pipeline(
    "fill-mask",
    model="gigilin7/agriculture-bert-base-chinese",
    tokenizer="gigilin7/agriculture-bert-base-chinese"
)
res = fill_mask("[MASK]是許多亞洲國家的主要糧食作物。")