Scifive Base Pubmed PMC

🚀 SciFive Pubmed+PMC Base

SciFive Pubmed+PMC Base是一個用於生物醫學文獻處理的文本到文本的變換器模型，可應用於多種自然語言處理任務，如令牌分類、文本分類、問答和文本生成等。

🚀 快速開始

對於更多詳細信息，請查看我們的GitHub倉庫。

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

基礎用法

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)

📚 詳細文檔

論文信息

論文：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

標籤與數據集