ethertech-healthcare-line-of-therapy-extractor

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alpeshsonar commited on Sep 4

Commit

5516ba5

•

1 Parent(s): a53fb22

Update app.py

Files changed (1) hide show

app.py CHANGED Viewed

@@ -12,7 +12,7 @@ tokenizer = T5Tokenizer.from_pretrained("alpeshsonar/lot-t5-small-filter", legac
 model = T5ForConditionalGeneration.from_pretrained("alpeshsonar/lot-t5-small-filter", torch_dtype=torch.bfloat16).to(device)
 # Gradio interface
-@spaces.GPU(duration=360)
 def generate_text(input_text):
     inputs = tokenizer.encode("Extract lots from given text.\n" + input_text, return_tensors="pt").to(device)
     outputs = model.generate(inputs, max_new_tokens=1024)

 model = T5ForConditionalGeneration.from_pretrained("alpeshsonar/lot-t5-small-filter", torch_dtype=torch.bfloat16).to(device)
 # Gradio interface
+@spaces.GPU(duration=120)
 def generate_text(input_text):
     inputs = tokenizer.encode("Extract lots from given text.\n" + input_text, return_tensors="pt").to(device)
     outputs = model.generate(inputs, max_new_tokens=1024)