Update app.py

app.py

@@ -13,7 +13,7 @@ You can use this ZeroGPU Space to test out the current model [intfloat/e5-mistra
 You can also use 🐣e5-mistral🛌🏻 by cloning this space. 🧬🔬🔍 Simply click here: <a style="display:inline-block" href="https://huggingface.co/spaces/Tonic/e5?duplicate=true"><img src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14" alt="Duplicate Space"></a></h3> 
 Join us : 🌟TeamTonic🌟 is always making cool demos! Join our active builder's🛠️community 👻  [![Join us on Discord](https://img.shields.io/discord/1109943800132010065?label=Discord&logo=discord&style=flat-square)](https://discord.gg/GWpVpekp) On 🤗Huggingface: [TeamTonic](https://huggingface.co/TeamTonic) & [MultiTransformer](https://huggingface.co/MultiTransformer) On 🌐Github: [Polytonic](https://github.com/tonic-ai) & contribute to 🌟 [Poly](https://github.com/tonic-ai/poly) 🤗Big thanks to Yuvi Sharma and all the folks at huggingface for the community grant 🤗
 """
-os.environ['PYTORCH_CUDA_ALLOC_CONF'] = 'max_split_size_mb:56'
+os.environ['PYTORCH_CUDA_ALLOC_CONF'] = 'max_split_size_mb:30'
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
 tasks = {
@@ -56,6 +56,7 @@ class EmbeddingModel:
         self.tokenizer = AutoTokenizer.from_pretrained('intfloat/e5-mistral-7b-instruct')
         self.model = AutoModel.from_pretrained('intfloat/e5-mistral-7b-instruct', torch_dtype=torch.float16, device_map=device)
     
+    @spaces.GPU
     def _compute_cosine_similarity(self, emb1, emb2):
         tensor1 = torch.tensor(emb1).to(device).half()
         tensor2 = torch.tensor(emb2).to(device).half()
@@ -140,7 +141,7 @@ def app_interface():
             similarity_output = gr.Label(label="🐣e5-mistral🛌🏻 Similarity Scores")
             similarity_button.click(
                 fn=embedding_model.compute_similarity,
-                inputs=[task_dropdown, sentence1_box, sentence2_box, extra_sentence1_box, extra_sentence2_box],
+                inputs=[task_dropdown, sentence1_box, sentence2_box],
                 outputs=similarity_output
             )