Update app.py

app.py

@@ -70,13 +70,13 @@ def clean_text_multithreaded(text):
 # Function to load the FastText model from Hugging Face
 @st.cache_resource
 def load_fasttext_model(model_dir):
-    model_path = os.path.join(model_dir, "fasttext_model.model")
-    vectors_path = os.path.join(model_dir, "fasttext_model_vectors.kv")
-    vectors_ngrams_path = os.path.join(model_dir, "fasttext_model.model.wv.vectors_ngrams.npy")
+    #model_path = os.path.join(model_dir, "fasttext_model.model")
+    #vectors_path = os.path.join(model_dir, "fasttext_model_vectors.kv")
+    #vectors_ngrams_path = os.path.join(model_dir, "fasttext_model.model.wv.vectors_ngrams.npy")
     
     model = FastText.load(model_path)
-    model.wv = KeyedVectors.load(vectors_path, mmap='r')
-    model.wv.vectors_ngrams = np.load(vectors_ngrams_path, mmap_mode='r')
+    #model.wv = KeyedVectors.load(vectors_path, mmap='r')
+    #model.wv.vectors_ngrams = np.load(vectors_ngrams_path, mmap_mode='r')
     
     return model
 
@@ -207,11 +207,11 @@ def main():
         st.header("Generate Embeddings with Pretrained FastText Model")
         
         repo_id = "Blessmore/Fasttext_embeddings/Fast_text_50_dim"
-        model_file = "fasttext_model.model"
+        model_file = "Fast_text_50_dim"
         vectors_file = "fasttext_model_vectors.kv"
         vectors_ngrams_file = "fasttext_model.model.wv.vectors_ngrams.npy"
 
-        model = load_fasttext_model(repo_id, model_file, vectors_file, vectors_ngrams_file)
+        model = load_fasttext_model(model_file)
 
         st.subheader("Generate Word Embedding")
         word = st.text_input("Enter a word:")