model name changes

Author: yil532

generativeai/extraction.py

@@ -18,7 +18,7 @@
 
 def extractive_question_answering(temperature=0):
     """Extractive Question Answering with a Large Language Model."""
-    model = TextGenerationModel.from_pretrained("google/text-bison@001")
+    model = TextGenerationModel.from_pretrained("text-bison@001")
     response = model.predict(
       '''Background: There is evidence that there have been significant changes \
 in Amazon rainforest vegetation over the last 21,000 years through the Last \

generativeai/ideation.py

@@ -18,7 +18,7 @@
 
 def interview(temperature=.2):
     """Ideation example with a Large Language Model"""
-    model = TextGenerationModel.from_pretrained("google/text-bison@001")
+    model = TextGenerationModel.from_pretrained("text-bison@001")
     response = model.predict(
         'Give me ten interview questions for the role of program manager.',
         temperature=temperature,

generativeai/list_tuned_models.py

@@ -23,7 +23,7 @@
 def list_tuned_models(project_id, location):
     """List tuned models."""
     aiplatform.init(project=project_id, location=location)
-    model = TextGenerationModel.from_pretrained("google/text-bison@001")
+    model = TextGenerationModel.from_pretrained("text-bison@001")
     tuned_model_names = model.list_tuned_model_names()
     print(tuned_model_names)
 # [END generativeai_sdk_list_tuned_models]

generativeai/sentiment_analysis.py

@@ -18,7 +18,7 @@
 
 def sentiment_analysis(temperature=0):
     """Sentiment analysis example with a Large Language Model."""
-    model = TextGenerationModel.from_pretrained("google/text-bison@001")
+    model = TextGenerationModel.from_pretrained("text-bison@001")
     response = model.predict(
       '''I had to compare two versions of Hamlet for my Shakespeare class and \
 unfortunately I picked this version. Everything from the acting (the actors \

generativeai/summarization.py

@@ -18,7 +18,7 @@
 
 def text_summarization(temperature=.2):
     """Summarization Example with a Large Language Model"""
-    model = TextGenerationModel.from_pretrained("google/text-bison@001")
+    model = TextGenerationModel.from_pretrained("text-bison@001")
     response = model.predict(
         '''Provide a summary with about two sentences for the following article:
 The efficient-market hypothesis (EMH) is a hypothesis in financial \

generativeai/tuning.py

@@ -47,7 +47,7 @@ def tuning(
     train_steps: Number of training steps to use when tuning the model.
   """
   aiplatform.init(project=project_id, location=location)
-  model = TextGenerationModel.from_pretrained("google/text-bison@001")
+  model = TextGenerationModel.from_pretrained("text-bison@001")
 
   model.tune_model(
     training_data=training_data,