Update app.py

app.py

@@ -20,13 +20,15 @@ nltk.download('stopwords')
 
 model_checkpoint = "marefa-nlp/marefa-mt-en-ar"
 tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
-#model = TFAutoModelForSeq2SeqLM.from_pretrained(model_checkpoint,from_pt=True)
-with zipfile.ZipFile("tf_model.zip", 'r') as zip_ref:
-    zip_ref.extractall("./marian_model/")
 
-model = TFAutoModelForSeq2SeqLM.from_pretrained("./marian_model/")
+with zipfile.ZipFile("model.zip", 'r') as zip_ref:
+    zip_ref.extractall("./marian_model/")
 
+# Define the model architecture
+model = TFAutoModelForSeq2SeqLM.from_pretrained(model_checkpoint, from_pt=True)
 
+# Load the weights from the .h5 file
+model.load_weights("./marian_model/model.weights.h5")
 
 # Load cleaned_word_embeddings
 with open("cleaned_word_embeddings.pkl", "rb") as f: