Update app.py

app.py

@@ -65,21 +65,22 @@ class Translators:
     def mitre(self):
         from transformers import AutoModel, AutoTokenizer
         tokenizer = AutoTokenizer.from_pretrained(self.model_name, trust_remote_code=True, use_fast=False)
-        model = AutoModel.from_pretrained(self.model_name, trust_remote_code=True).to(self.device)
-        # model.half() # recommended
+        # model = AutoModel.from_pretrained(self.model_name, trust_remote_code=True).to(self.device)
+        model = AutoModel.from_pretrained(self.model_name, trust_remote_code=True)
+        model.half() # recommended
         model.eval()
-
         # Translating from one or several sentences to a sole language
         src_tokens = tokenizer.encode_source_tokens_to_input_ids([self.input_text, ], target_language=self.tl)
-        src_tokens = src_tokens.to(self.device)
+        # src_tokens = src_tokens.to(self.device)
+        generated_tokens = model.generate(src_tokens)
+        return tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)        
         # Translating from one or several sentences to corresponding languages
         # src_tokens = tokenizer.encode_source_tokens_to_input_ids_with_different_tags([english_text, english_text, ], target_languages_list=["de", "zh", ])      
-        # generated_tokens = model.generate(src_tokensto(self.device))
+        # generated_tokens = model.generate(src_tokens.to(self.device))
         # results = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
-        
-        with torch.no_grad():
-            generated_tokens = model.generate(src_tokens)
-        return tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
+        # with torch.no_grad():
+        #     generated_tokens = model.generate(src_tokens)
+        # return tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
     
     def hplt(self, opus = False):
         # langs = ['ar', 'bs', 'ca', 'en', 'et', 'eu', 'fi', 'ga', 'gl', 'hi', 'hr', 'is', 'mt', 'nn', 'sq', 'sw', 'zh_hant']