Update app.py

app.py

@@ -68,13 +68,12 @@ class EmbeddingModel:
 
     @spaces.GPU
     def compute_similarity(self, sentence1, sentence2, extra_sentence1, extra_sentence2):
-        # Tokenize and encode sentences
+
         sentences = [sentence1, sentence2, extra_sentence1, extra_sentence2]
         encoded_input = self.tokenizer(sentences, padding=True, truncation=True, return_tensors='pt').to(device)
         with torch.no_grad():
             model_output = self.model(**encoded_input)
 
-        # Compute embeddings
         embeddings = last_token_pool(model_output.last_hidden_state, encoded_input['attention_mask'])
         embeddings = F.normalize(embeddings, p=2, dim=1)
 
@@ -88,9 +87,10 @@ def app_interface():
     with gr.Blocks() as demo:
         gr.Markdown(title)
         gr.Markdown(description)
+        with gr.Row():
+            task_dropdown = gr.Dropdown(list(tasks.keys()), label="Select a Task", value=list(tasks.keys())[0])
 
         with gr.Tab("Embedding Generation"):
-            task_dropdown = gr.Dropdown(list(tasks.keys()), label="Select a Task", value=list(tasks.keys())[0])
             input_text_box = gr.Textbox(label="📖Input Text")
             system_prompt_box = gr.Textbox(label="🤖System Prompt (Optional)")
             compute_button = gr.Button("Try🐣🛌🏻e5")
@@ -104,8 +104,8 @@ def app_interface():
         with gr.Tab("Sentence Similarity"):
             sentence1_box = gr.Textbox(label="Sentence 1")
             sentence2_box = gr.Textbox(label="Sentence 2")
-            extra_sentence1_box = gr.Textbox(label="Extra Sentence 1")
-            extra_sentence2_box = gr.Textbox(label="Extra Sentence 2")
+            extra_sentence1_box = gr.Textbox(label="Sentence 3")
+            extra_sentence2_box = gr.Textbox(label="Sentence 4")
             similarity_button = gr.Button("Compute Similarity")
             similarity_output = gr.Label(label="🐣e5-mistral🛌🏻 Similarity Scores")
             similarity_button.click(