Scifive Base Pubmed PMC

🚀 SciFive Pubmed+PMC Base

SciFive Pubmed+PMC Base是一个用于生物医学文献处理的文本到文本的变换器模型，可应用于多种自然语言处理任务，如令牌分类、文本分类、问答和文本生成等。

🚀 快速开始

对于更多详细信息，请查看我们的GitHub仓库。

from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("razent/SciFive-base-Pubmed_PMC")  
model = AutoModelForSeq2SeqLM.from_pretrained("razent/SciFive-base-Pubmed_PMC")

sentence = "Identification of APC2 , a homologue of the adenomatous polyposis coli tumour suppressor ."
text =  sentence + "</s>"

encoding = tokenizer.encode_plus(text, pad_to_max_length=True, return_tensors="pt")
input_ids, attention_masks = encoding["input_ids"].to("cuda"), encoding["attention_mask"].to("cuda")

outputs = model.generate(
    input_ids=input_ids, attention_mask=attention_masks,
    max_length=256,
    early_stopping=True
)

for output in outputs:
    line = tokenizer.decode(output, skip_special_tokens=True, clean_up_tokenization_spaces=True)
    print(line)

💻 使用示例

基础用法

from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("razent/SciFive-base-Pubmed_PMC")  
model = AutoModelForSeq2SeqLM.from_pretrained("razent/SciFive-base-Pubmed_PMC")

sentence = "Identification of APC2 , a homologue of the adenomatous polyposis coli tumour suppressor ."
text =  sentence + "</s>"

encoding = tokenizer.encode_plus(text, pad_to_max_length=True, return_tensors="pt")
input_ids, attention_masks = encoding["input_ids"].to("cuda"), encoding["attention_mask"].to("cuda")

outputs = model.generate(
    input_ids=input_ids, attention_mask=attention_masks,
    max_length=256,
    early_stopping=True
)

for output in outputs:
    line = tokenizer.decode(output, skip_special_tokens=True, clean_up_tokenization_spaces=True)
    print(line)

📚 详细文档

论文信息

论文：SciFive: a text-to-text transformer model for biomedical literature 作者：Long N. Phan, James T. Anibal, Hieu Tran, Shaurya Chanana, Erol Bahadroglu, Alec Peltekian, Grégoire Altan-Bonnet

标签与数据集