
# SciFive Pubmed+PMC Large

## Introduction
Paper: [SciFive: a text-to-text transformer model for biomedical literature](https://arxiv.org/abs/2106.03598)

Authors: _Long N. Phan, James T. Anibal, Hieu Tran, Shaurya Chanana, Erol Bahadroglu, Alec Peltekian, Grégoire Altan-Bonnet_

## How to use
For more details, do check out [our Github repo](https://github.com/justinphan3110/SciFive). 
```python
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
​
tokenizer = AutoTokenizer.from_pretrained("razent/SciFive-large-Pubmed_PMC")  
model = AutoModelForSeq2SeqLM.from_pretrained("razent/SciFive-large-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)
```
{"language": ["en"], "tags": ["token-classification", "text-classification", "question-answering", "text2text-generation", "text-generation"], "datasets": ["pubmed", "pmc/open_access"]}
transformers pytorch tf t5 text2text-generation token-classification text-classification question-answering text-generation en dataset:pubmed dataset:pmc/open_access arxiv:2106.03598 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tf #t5 #text2text-generation #token-classification #text-classification #question-answering #text-generation #en #dataset-pubmed #dataset-pmc/open_access #arxiv-2106.03598 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 


# SciFive Pubmed+PMC Large

## Introduction
Paper: SciFive: a text-to-text transformer model for biomedical literature

Authors: _Long N. Phan, James T. Anibal, Hieu Tran, Shaurya Chanana, Erol Bahadroglu, Alec Peltekian, Grégoire Altan-Bonnet_

## How to use
For more details, do check out our Github repo. 

# SciFive Pubmed+PMC Large ## Introduction
Paper: SciFive: a text-to-text transformer model for biomedical literature

Authors: _Long N. Phan, James T. Anibal, Hieu Tran, Shaurya Chanana, Erol Bahadroglu, Alec Peltekian, Grégoire Altan-Bonnet_ ## How to use
For more details, do check out our Github repo.
TAGS
#transformers #pytorch #tf #t5 #text2text-generation #token-classification #text-classification #question-answering #text-generation #en #dataset-pubmed #dataset-pmc/open_access #arxiv-2106.03598 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # SciFive Pubmed+PMC Large ## Introduction
Paper: SciFive: a text-to-text transformer model for biomedical literature

Authors: _Long N. Phan, James T. Anibal, Hieu Tran, Shaurya Chanana, Erol Bahadroglu, Alec Peltekian, Grégoire Altan-Bonnet_ ## How to use
For more details, do check out our Github repo.
passage: TAGS
#transformers #pytorch #tf #t5 #text2text-generation #token-classification #text-classification #question-answering #text-generation #en #dataset-pubmed #dataset-pmc/open_access #arxiv-2106.03598 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# SciFive Pubmed+PMC Large## Introduction
Paper: SciFive: a text-to-text transformer model for biomedical literature

Authors: _Long N. Phan, James T. Anibal, Hieu Tran, Shaurya Chanana, Erol Bahadroglu, Alec Peltekian, Grégoire Altan-Bonnet_## How to use
For more details, do check out our Github repo.