模型:
cahya/t5-base-indonesian-summarization-cased
为印尼进行微调的 T5 基础摘要模型。
t5-base-indonesian-summarization-cased 模型基于 t5-base-bahasa-summarization-cased,由 huseinzol05 进行微调,使用 id_liputan6 数据集。
from transformers import T5Tokenizer, T5Model, T5ForConditionalGeneration tokenizer = T5Tokenizer.from_pretrained("cahya/t5-base-indonesian-summarization-cased") model = T5ForConditionalGeneration.from_pretrained("cahya/t5-base-indonesian-summarization-cased")
from transformers import T5Tokenizer, T5ForConditionalGeneration tokenizer = T5Tokenizer.from_pretrained("cahya/t5-base-indonesian-summarization-cased") model = T5ForConditionalGeneration.from_pretrained("cahya/t5-base-indonesian-summarization-cased") # ARTICLE_TO_SUMMARIZE = "" # generate summary input_ids = tokenizer.encode(ARTICLE_TO_SUMMARIZE, return_tensors='pt') summary_ids = model.generate(input_ids, min_length=20, max_length=80, num_beams=10, repetition_penalty=2.5, length_penalty=1.0, early_stopping=True, no_repeat_ngram_size=2, use_cache=True, do_sample = True, temperature = 0.8, top_k = 50, top_p = 0.95) summary_text = tokenizer.decode(summary_ids[0], skip_special_tokens=True) print(summary_text)
输出: