Update app.py

app.py

@@ -1,4 +1,3 @@
-import spaces
 import torch
 import torch.nn.functional as F
 from torch import Tensor
@@ -82,8 +81,6 @@ def embedding_worker():
 
 threading.Thread(target=embedding_worker, daemon=True).start()
 
-
-@spaces.GPU
 def compute_embeddings(selected_task, input_text):
     try:
         task_description = tasks[selected_task]
@@ -104,7 +101,6 @@ def compute_embeddings(selected_task, input_text):
     clear_cuda_cache()
     return embeddings_list
 
-@spaces.GPU
 def decode_embedding(embedding_str):
     try:
         embedding = [float(num) for num in embedding_str.split(',')]
@@ -114,7 +110,6 @@ def decode_embedding(embedding_str):
     except Exception as e:
         return f"Error in decoding: {str(e)}"
 
-@spaces.GPU
 def compute_similarity(selected_task, sentence1, sentence2, extra_sentence1, extra_sentence2):
     try:
         task_description = tasks[selected_task]
@@ -145,7 +140,6 @@ def compute_similarity(selected_task, sentence1, sentence2, extra_sentence1, ext
     clear_cuda_cache()
     return similarity_scores
     
-@spaces.GPU
 def compute_cosine_similarity(emb1, emb2):
     tensor1 = torch.tensor(emb1).to(device).half()
     tensor2 = torch.tensor(emb2).to(device).half()
@@ -155,7 +149,6 @@ def compute_cosine_similarity(emb1, emb2):
     return similarity
 
 
-@spaces.GPU
 def compute_embeddings_batch(input_texts):
     max_length = 2042
     processed_texts = [f'Instruct: {task_description}\nQuery: {text}' for text in input_texts]
@@ -311,4 +304,4 @@ def app_interface():
     return demo
 
 app_interface().queue()
-app_interface().launch()
+app_interface().launch(share=True)