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src/myNLI.py

@@ -26,8 +26,8 @@ class FactChecker:
         self.envir = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')
 
         # Load LLM
-        self.tokenizer = AutoTokenizer.from_pretrained("MoritzLaurer/mDeBERTa-v3-base-mnli-xnli")    # LOAD mDEBERTa TOKENIZER
-        self.mDeBertaModel = AutoModel.from_pretrained(f"src/mDeBERTa (ft) V6/mDeBERTa-v3-base-mnli-xnli-{self.INPUT_TYPE}")  # LOAD FINETUNED MODEL
+        self.tokenizer = AutoTokenizer.from_pretrained("MoritzLaurer/mDeBERTa-v3-base-mnli-xnli", use_auth_token=False)    # LOAD mDEBERTa TOKENIZER
+        self.mDeBertaModel = AutoModel.from_pretrained(f"src/mDeBERTa (ft) V6/mDeBERTa-v3-base-mnli-xnli-{self.INPUT_TYPE}", use_auth_token=False)  # LOAD FINETUNED MODEL
         # Load classifier model
         self.checkpoints = torch.load(f"src/mDeBERTa (ft) V6/{self.INPUT_TYPE}.pt", map_location=self.envir)