metadata

language: zh
tags:
  - agriculture-domain
  - agriculture
widget:
  - text: '[MASK]是許多亞洲國家的主要糧食作物。'

agriculture-bert-base-chinese

This is a bert model for agriculture domain. The self-supervised learning approach of MLM was used to train the model.

Masked language modeling (MLM): taking a sentence, the model randomly masks 15% of the words in the input then run the entire masked sentence through the model and has to predict the masked words.
This is different from traditional recurrent neural networks (RNNs) that usually see the words one after the other, or from autoregressive models like GPT internally masks the future tokens.
It allows the model to learn a bidirectional representation of the sentence.

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。")