Remove redundant text encoder model download and update tokenizer path in app.py

app.py

@@ -44,13 +44,6 @@ def download_weights(weights_path):
         if not vae_file.exists():
             hf_hub_download(repo_id="FoundationVision/Infinity", filename="infinity_vae_d32reg.pth", local_dir=str(weights_path))
         
-        # For the text encoder, we need to download the entire model
-        text_encoder_ckpt = weights_path / 'flan-t5-xl'
-        if not text_encoder_ckpt.exists():
-            tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-xl")
-            model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-xl")
-            tokenizer.save_pretrained(text_encoder_ckpt)
-            model.save_pretrained(text_encoder_ckpt)
     except Exception as e:
         print(f"Error downloading weights: {e}")
 
@@ -402,7 +395,7 @@ args = argparse.Namespace(
 )
 
 # Load models
-text_tokenizer, text_encoder = load_tokenizer(t5_path=str(weights_path / 'flan-t5-xl'))
+text_tokenizer, text_encoder = load_tokenizer(t5_path="google/flan-t5-xl")
 vae = load_visual_tokenizer(args)
 infinity = load_transformer(vae, args)