
# SciFive Pubmed+PMC Large on MedNLI

## Introduction

Finetuned SciFive Pubmed+PMC Large model achieved state-of-the-art results on [MedNLI (Medical Natural Language Inference)](https://paperswithcode.com/sota/natural-language-inference-on-mednli)

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-MedNLI")  
model = AutoModelForSeq2SeqLM.from_pretrained("razent/SciFive-large-Pubmed_PMC-MedNLI")
model.cuda()
​
sent_1 = "In the ED, initial VS revealed T 98.9, HR 73, BP 121/90, RR 15, O2 sat 98% on RA."
sent_2 = "The patient is hemodynamically stable"
text =  f"mednli: sentence1: {sent_1} sentence2: {sent_2}"

encoding = tokenizer.encode_plus(text, padding='max_length', max_length=256, 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=8,
    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": ["text2text-generation", "mednli"], "datasets": ["pubmed", "pmc/open_access"], "widget": [{"text": "mednli: sentence1: In the ED, initial VS revealed T 98.9, HR 73, BP 121/90, RR 15, O2 sat 98% on RA. sentence2: The patient is hemodynamically stable"}]}
transformers pytorch tf t5 text2text-generation mednli 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 #mednli #en #dataset-pubmed #dataset-pmc/open_access #arxiv-2106.03598 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 


# SciFive Pubmed+PMC Large on MedNLI

## Introduction

Finetuned SciFive Pubmed+PMC Large model achieved state-of-the-art results on MedNLI (Medical Natural Language Inference)

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 on MedNLI ## Introduction

Finetuned SciFive Pubmed+PMC Large model achieved state-of-the-art results on MedNLI (Medical Natural Language Inference)

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 #mednli #en #dataset-pubmed #dataset-pmc/open_access #arxiv-2106.03598 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # SciFive Pubmed+PMC Large on MedNLI ## Introduction

Finetuned SciFive Pubmed+PMC Large model achieved state-of-the-art results on MedNLI (Medical Natural Language Inference)

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 #mednli #en #dataset-pubmed #dataset-pmc/open_access #arxiv-2106.03598 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# SciFive Pubmed+PMC Large on MedNLI## Introduction

Finetuned SciFive Pubmed+PMC Large model achieved state-of-the-art results on MedNLI (Medical Natural Language Inference)

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.