Update app.py

app.py

@@ -65,7 +65,7 @@ def NMRExtractor(Paragraph, max_length):
     
     pipe = pipeline(task="text-generation", model=base_model, tokenizer=tokenizer, max_length=max_length)
     print('prompt',prompt)
-    result = pipe(f"{prompt}",max_length=1024,truncation=True)
+    result = pipe(f"{prompt}",max_length=max_length,truncation=True)
     print('result',result)
     generation = result[0]['generated_text']
     print('generation',generation) 
@@ -123,7 +123,7 @@ demo = gr.Interface(
     💡 We have released the GPU version code of NMRExtractor on github, and the inference speed is an average of 0.5 seconds per item. https://github.com/.../NMRExtractor\n
     ✏️1. Enter your text or click to select one from the examples below.\n
     📀2. Set parameters: "max_length": modify according to the length of the text you enter.\n
-    🏆3. After clicking submit, wait about 300 seconds⏰.
+    🏆3. After clicking submit, because the CPU runs very slowly, you need to wait for a long time⏰.
     """,
                     
     article = 'https://github.com/.../NMRExtractor',