Update app.py

app.py

@@ -1,18 +1,14 @@
-import gradio as gr
-import os 
-import numpy as np 
-
-import keras_nlp
-preprocessor = keras_nlp.models.GemmaPreprocessor.from_preset(
-    "gemma_2b_en", sequence_length=64
-)
-model = keras_nlp.models.GemmaBackbone.from_preset("gemma_2b_en")
-
+from transformers import AutoTokenizer, GemmaForSequenceClassification
 
+import os 
+model = GemmaForSequenceClassification.from_pretrained("google/gemma-2b")
+tokenizer = AutoTokenizer.from_pretrained("google/gemma-2b")
 def greet(name):
-  x = preprocessor(name)
-  lab = model(x)
-  return lab
+  x = tokenizer(name,return_tensors='pt')
+  with torch.no_grad():
+      preds = model(**inputs)
+  
+  return preds
 
 iface = gr.Interface(fn=greet, inputs="text", outputs="text")
 iface.launch()