模型:
allenai/t5-small-next-word-generator-qoogle
基于问题训练的下一个单词生成器。接收到部分问题并尝试预测下一个单词。示例用法:
from transformers import T5Config, T5ForConditionalGeneration, T5Tokenizer model_name = "allenai/t5-small-next-word-generator-qoogle" tokenizer = T5Tokenizer.from_pretrained(model_name) model = T5ForConditionalGeneration.from_pretrained(model_name) def run_model(input_string, **generator_args): input_ids = tokenizer.encode(input_string, return_tensors="pt") res = model.generate(input_ids, **generator_args) output = tokenizer.batch_decode(res, skip_special_tokens=True) print(output) return output run_model("Which") run_model("Which two") run_model("Which two counties") run_model("Which two counties are") run_model("Which two counties are the") run_model("Which two counties are the biggest") run_model("Which two counties are the biggest economic") run_model("Which two counties are the biggest economic powers")
将得到以下结果:
['one'] ['statements'] ['are'] ['in'] ['most'] ['in'] ['zones'] ['of']