Update app.py

app.py

@@ -9,43 +9,49 @@ import pandas as pd
 # from data_5_LT23 import features_dict,extra_feature_dict
 from data_predict import convert_to_stsb_features,convert_to_features
 
+from huggingface_hub import hf_hub_download,snapshot_download
+
+
 features_dict = {}
 extra_feature_dict = {}
 sentinews_location = ""
 
-df_document_croatian_test = pd.read_csv(sentinews_location+"textlabel.tsv", sep="\t")
-df_document_croatian_test = df_document_croatian_test[["content"]]
-
-# gather everyone if you want to have a single DatasetDict
-document = DatasetDict({
-    # "train": Dataset.from_pandas(df_document_sl_hr_train),
-    # "valid": Dataset.from_pandas(df_document_sl_hr_valid),
-    "test": Dataset.from_pandas(df_document_croatian_test)
-})
-
-dataset_dict = {
-    "document": document,
-}
-
-for task_name, dataset in dataset_dict.items():
-    print(task_name)
-    print(dataset_dict[task_name]["test"][0])
-    print()
-
-
-convert_func_dict = {
-    "document": convert_to_stsb_features,
-    # "paragraph": convert_to_stsb_features,
-    # "sentence": convert_to_stsb_features,
-}
+# df_document_croatian_test = pd.read_csv(sentinews_location+"textlabel.tsv", sep="\t")
+# df_document_croatian_test = df_document_croatian_test[["content"]]
+def predict():
+    # gather everyone if you want to have a single DatasetDict
+    document = DatasetDict({
+        # "train": Dataset.from_pandas(df_document_sl_hr_train),
+        # "valid": Dataset.from_pandas(df_document_sl_hr_valid),
+        "test": Dataset.from_dict({"content":["Volim ti"]})
+    })
+    
+    dataset_dict = {
+        "document": document,
+    }
+    
+    for task_name, dataset in dataset_dict.items():
+        print(task_name)
+        print(dataset_dict[task_name]["test"][0])
+        print()
+    
+    
+    convert_func_dict = {
+        "document": convert_to_stsb_features,
+        # "paragraph": convert_to_stsb_features,
+        # "sentence": convert_to_stsb_features,
+    }
+    
+    features_dict = convert_to_features(dataset_dict, convert_func_dict)
 
-features_dict = convert_to_features(dataset_dict, convert_func_dict)
 
 
+#model_link = snapshot_download(repo_id="FFZG-cleopatra/Croatian-News-Classifier")
+model_link = hf_hub_download(repo_id="FFZG-cleopatra/Croatian-News-Classifier",filename = "pytorch_model.bin")
 
 # multitask_model.from_pretrained(, config="/media/gaurish/angela/projects/CroatianSlovenEnglishBert/i-got-u-brother-cleopatra-workshop/src/models/multitask_model_3ep/config.json")
 multitask_model.load_state_dict(torch.load(
-    "multitask_model_3ep/pytorch_model.bin"
+   model_link #"multitask_model_3ep/pytorch_model.bin"
     ))
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 multitask_model.to(device)