Update app.py

app.py

@@ -9,6 +9,7 @@ import unicodedata
 import re
 from tqdm import tqdm
 import gradio as gr 
+from huggingface_hub import hf_hub_download 
 
 # Device configuration: consistent device for model and tensors
 device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
@@ -114,9 +115,12 @@ class RNN(nn.Module):
             h = h[-1]
         return self.fc(self.dropout(h))
 
+model_path = hf_hub_download(repo_id="Di12/sentiment_analysis", filename="model.pt")
+embedding_path = hf_hub_download(repo_id="Di12/sentiment_analysis", filename="vi_word2vec.txt")
+
 # Load pretrained embeddings and build vocab
 word_embedding = vocab.Vectors(
-    name='/content/drive/MyDrive/Colab Notebooks/Data/Sentiment Analysis/vi_word2vec.txt',
+    name=embedding_path,
     unk_init=torch.Tensor.normal_
 )
 vocab = Vocabulary()
@@ -142,7 +146,7 @@ def load_model(path: str):
     model.eval()
     return model
 
-model = load_model('/content/drive/MyDrive/Colab Notebooks/Data/Sentiment Analysis/model.pt')
+model = load_model(model_path)
 
 # Prediction helper
 def predict_sentiment(model, sentence, vocab, label_mapping=None):