Update app.py

app.py

@@ -44,7 +44,7 @@ pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=dtype).to("cuda
 #pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taef1", torch_dtype=torch.float16).to("cuda")
 torch.cuda.empty_cache()
 
-clipmodel = 'norm'
+clipmodel = 'long'
 if clipmodel == "long":
     model_id = "zer0int/LongCLIP-GmP-ViT-L-14"
     config = CLIPConfig.from_pretrained(model_id)
@@ -55,13 +55,13 @@ if clipmodel == "norm":
     maxtokens = 77
 clip_model = CLIPModel.from_pretrained(model_id, torch_dtype=torch.bfloat16, config=config, ignore_mismatched_sizes=True).to("cuda")
 clip_processor = CLIPProcessor.from_pretrained(model_id, padding="max_length", max_length=maxtokens, ignore_mismatched_sizes=True, return_tensors="pt", truncation=True)
-t5 = HFEmbedder("DeepFloyd/t5-v1_1-xxl", max_length=512, torch_dtype=torch.bfloat16).to(device)
+#t5 = HFEmbedder("DeepFloyd/t5-v1_1-xxl", max_length=512, torch_dtype=torch.bfloat16).to(device)
 
 pipe.tokenizer = clip_processor.tokenizer
 pipe.text_encoder = clip_model.text_model
 pipe.tokenizer_max_length = maxtokens
 pipe.text_encoder.dtype = torch.bfloat16
-pipe.text_encoder_2 = t5.text_model
+#pipe.text_encoder_2 = t5.text_model
 
 MAX_SEED = 2**32-1