send application for test

app.py

@@ -25,7 +25,12 @@ models = {
             "checkpoints": "wolof-translate/wolof_translate/checkpoints/t5_small_custom_train_results_fw_v3",
             "tokenizer": "wolof-translate/wolof_translate/tokenizers/t5_tokenizers/tokenizer_v3.json",
             "max_len": 51
-            }
+            },
+        "Wolof ➡️ French": {
+            "checkpoints": "wolof-translate/wolof_translate/checkpoints/t5_small_custom_train_results_wf_v3",
+            "tokenizer": "wolof-translate/wolof_translate/trokenizers/t5_tokenizers/tokenizer_v3.json",
+            "max_len": 51
+        }
     }
 }
 
@@ -43,36 +48,62 @@ temperature = st.sidebar.slider("How randomly need you the translated sentences
 
 # make the process
 try:
-    # recuperate checkpoints
-    checkpoints = torch.load(os.path.join(models[version][translation_type]['checkpoints'], "best_checkpoints.pth"), map_location=torch.device('cpu'))
-
-    # recuperate the tokenizer
-    tokenizer_file = models[version][translation_type]['tokenizer']
     
     # recuperate the max length
     max_len = models[version][translation_type]['max_len']
     
     # let us get the best model
     @st.cache_resource
-    def get_model():
+    def get_modelfw_v3():
+        
+        # recuperate checkpoints
+        checkpoints = torch.load(os.path.join('wolof-translate/wolof_translate/checkpoints/t5_small_custom_train_results_fw_v3', "best_checkpoints.pth"), map_location=torch.device('cpu'))
+        
+        # recuperate the tokenizer
+        tokenizer_file = "wolof-translate/wolof_translate/tokenizers/t5_tokenizers/tokenizer_v3.json"
         
         # initialize the tokenizer
         tokenizer = T5TokenizerFast(tokenizer_file=tokenizer_file)
         
-        # initialize the model
-        model_name = 't5-small'
-        
-        model = T5ForConditionalGeneration.from_pretrained(model_name)
+        model = T5ForConditionalGeneration.from_pretrained('t5-small')
         
         # resize the token embeddings
         model.resize_token_embeddings(len(tokenizer))
         
         model.load_state_dict(checkpoints['model_state_dict'])
         
+        return model, tokenizer
+    
+    @st.cache_resource
+    def get_modelwf_v3():
+        
+        # recuperate checkpoints
+        checkpoints = torch.load(os.path.join('wolof-translate/wolof_translate/checkpoints/t5_small_custom_train_results_wf_v3', "best_checkpoints.pth"), map_location=torch.device('cpu'))
+        
+        # recuperate the tokenizer
+        tokenizer_file = "wolof-translate/wolof_translate/tokenizers/t5_tokenizers/tokenizer_v3.json"
+        
+        # initialize the tokenizer
+        tokenizer = T5TokenizerFast(tokenizer_file=tokenizer_file)
+        
+        model = T5ForConditionalGeneration.from_pretrained('t5-small')
+        
+        # resize the token embeddings
+        model.resize_token_embeddings(len(tokenizer))
+        
+        model.load_state_dict(checkpoints['model_state_dict'])
         
         return model, tokenizer
 
-    model, tokenizer = get_model()
+    if version == "Version ☝️":
+        
+        if translation_type == "French ➡️ Wolof":
+            
+            model, tokenizer = get_modelfw_v3()
+        
+        elif translation_type == "Wolof ➡️ French":
+            
+            model, tokenizer = get_modelwf_v3() 
 
     # set the model to eval mode
     _ = model.eval()

wolof-translate/wolof_translate/checkpoints/t5_small_custom_train_results_wf_v3/best_checkpoints.json

@@ -0,0 +1,13 @@
+{
+    "metrics": {
+        "train_loss": 0.010352298853033019,
+        "test_loss": 0.5878886595368386,
+        "bleu": 22.9625,
+        "gen_len": 9.3562,
+        "current_epoch": 94
+    },
+    "best_performance": {
+        "best_score": 22.9625,
+        "best_epoch": 94
+    }
+}

wolof-translate/wolof_translate/checkpoints/t5_small_custom_train_results_wf_v3/best_checkpoints.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0427e418e75d5842f8b95ebe9025e91d6e16dd79ab7d6f5815320e239e8b350f
+size 180980359