razent
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SciFive-large-PMC

Text Classification

text2text-generation

token-classification

question-answering

text-generation

text-generation-inference

Inference Endpoints

Model card Files Files and versions Community

justinphan3110 commited on Nov 26, 2022

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@@ -29,7 +29,7 @@ tokenizer = AutoTokenizer.from_pretrained("razent/SciFive-large-PMC")
 model = AutoModelForSeq2SeqLM.from_pretrained("razent/SciFive-large-PMC")
 sentence = "Identification of APC2 , a homologue of the adenomatous polyposis coli tumour suppressor ."
-text =  "ncbi_ner: " + 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")

 model = AutoModelForSeq2SeqLM.from_pretrained("razent/SciFive-large-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")