Update app.py

app.py

@@ -29,7 +29,7 @@ from fudge.constants import *
 
 
 # imp.reload(model)
-pretrained_model = "../checkpoint-150/"
+pretrained_model = "checkpoint-150/"
 generation_model = AutoModelForSeq2SeqLM.from_pretrained(pretrained_model, return_dict=True).to(device)
 
 device = 'cuda'
@@ -40,7 +40,7 @@ generation_model.eval()
 model_args = mock.Mock()
 model_args.task = 'clickbait'
 model_args.device = device
-model_args.checkpoint = '../checkpoint-1464/'
+model_args.checkpoint = 'checkpoint-1464/'
 
 # conditioning_model = Model(model_args, pad_id, len(dataset_info.index2word)) # no need to get the glove embeddings when reloading since they're saved in model ckpt anyway
 conditioning_model = Model(model_args, pad_id, vocab_size=None) # no need to get the glove embeddings when reloading since they're saved in model ckpt anyway