Update app.py

app.py

@@ -9,10 +9,6 @@ from transformers import ImageClassificationPipeline, PerceiverForImageClassific
 from transformers import VisionEncoderDecoderModel
 from transformers import AutoTokenizer
 import torch
-
-# https://github.com/NielsRogge/Transformers-Tutorials/blob/master/HuggingFace_vision_ecosystem_overview_(June_2022).ipynb
-# option 1: load with randomly initialized weights (train from scratch)
-
 from transformers import (
     AutoModelForCausalLM,
     LogitsProcessorList,
@@ -21,11 +17,11 @@ from transformers import (
     MaxLengthCriteria,
 )
 
+# https://github.com/NielsRogge/Transformers-Tutorials/blob/master/HuggingFace_vision_ecosystem_overview_(June_2022).ipynb
+# option 1: load with randomly initialized weights (train from scratch)
 
-
-
-
-
+tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-j-6B")
+model = AutoModelForCausalLM.from_pretrained("EleutherAI/gpt-j-6B")
 
 
 config = ViTConfig(num_hidden_layers=12, hidden_size=768)
@@ -44,8 +40,11 @@ model = PerceiverForImageClassificationConvProcessing.from_pretrained("deepmind/
 image_pipe = ImageClassificationPipeline(model=model, feature_extractor=feature_extractor)
 
 def create_story(text_seed):
-  tokenizer = AutoTokenizer.from_pretrained("gpt2")
-  model = AutoModelForCausalLM.from_pretrained("gpt2")
+  #tokenizer = AutoTokenizer.from_pretrained("gpt2")
+  #model = AutoModelForCausalLM.from_pretrained("gpt2")
+  
+  tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-j-6B")
+  model = AutoModelForCausalLM.from_pretrained("EleutherAI/gpt-j-6B")
 
   # set pad_token_id to eos_token_id because GPT2 does not have a EOS token
   model.config.pad_token_id = model.config.eos_token_id