Update app.py

app.py

@@ -23,6 +23,11 @@ os.environ["TRANSFORMERS_CACHE"] = cache_path
 os.environ["HF_HUB_CACHE"] = cache_path
 os.environ["HF_HOME"] = cache_path
 
+
+torch.backends.cuda.matmul.allow_tf32 = True
+
+pipe = FluxPipeline.from_pretrained("AlekseyCalvin/HistoricColorSoonr_v2_FluxSchnell_Diffusers", ignore_mismatched_sizes=True, torch_dtype=torch.bfloat16)
+pipe.to(device="cuda", dtype=torch.bfloat16)
 clipmodel = 'long' # 'norm', 'long' (my fine-tunes) - 'oai', 'orgL' (OpenAI / BeichenZhang original)
 selectedprompt = 'long' # 'tiny' (51 tokens), 'short' (75), 'med' (116), 'long' (203)
 
@@ -30,17 +35,10 @@ if clipmodel == "long":
     model_id = "zer0int/LongCLIP-GmP-ViT-L-14"
     config = CLIPConfig.from_pretrained(model_id)
     maxtokens = 248
-
-torch.backends.cuda.matmul.allow_tf32 = True
-
 clip_model = CLIPModel.from_pretrained(model_id, torch_dtype=torch.bfloat16, config=config, ignore_mismatched_sizes=True).to(device)
 clip_processor = CLIPProcessor.from_pretrained(model_id, padding="max_length", max_length=maxtokens, ignore_mismatched_sizes=True, return_tensors="pt", truncation=True)
 config.text_config.max_position_embeddings = 248
 
-
-pipe = FluxPipeline.from_pretrained("AlekseyCalvin/HistoricColorSoonr_v2_FluxSchnell_Diffusers", ignore_mismatched_sizes=True, torch_dtype=torch.bfloat16)
-pipe.to(device="cuda", dtype=torch.bfloat16)
-
 pipe.tokenizer = clip_processor.tokenizer
 pipe.text_encoder = clip_model.text_model
 pipe.tokenizer_max_length = maxtokens