Update src/models/predict_model.py

src/models/predict_model.py

@@ -8,7 +8,7 @@ tqdm.pandas()
 from datasets import load_dataset
 
 df_wiki_windows = load_dataset("foxxy-hm/e2eqa-wiki",  data_files="processed/wikipedia_20220620_cleaned_v2.csv")["train"].to_pandas()
-df_wiki = load_dataset("foxxy-hm/e2eqa-wiki",  data_files="processed/wikipedia_20220620_short.csv")["train"].to_pandas()
+df_wiki = load_dataset("foxxy-hm/e2eqa-wiki",  data_files="wikipedia_20220620_short.csv")["train"].to_pandas()
 df_wiki.title = df_wiki.title.apply(str)
 
 entity_dict = load_dataset("foxxy-hm/e2eqa-wiki",  data_files="processed/entities.json")["train"].to_dict()
@@ -21,7 +21,7 @@ for key, val in entity_dict.items():
 entity_dict.update(new_dict)
 title2idx = dict([(x.strip(), y) for x, y in zip(df_wiki.title, df_wiki.index.values)])
 
-qa_model = QAEnsembleModel("nguyenvulebinh/vi-mrc-large", ["src/models/qa_model_robust.bin"], entity_dict)
+qa_model = QAEnsembleModel("nguyenvulebinh/vi-mrc-large", ["/src/models/qa_model_robust.bin"], entity_dict)
 pairwise_model_stage1 = PairwiseModel("nguyenvulebinh/vi-mrc-base").half()
 pairwise_model_stage1.load_state_dict(torch.load("/src/models/pairwise_v2.bin"))
 pairwise_model_stage1.eval()