Update README.md

README.md

@@ -28,22 +28,18 @@ This repository contains a fine-tuned version of `MoritzLaurer/mDeBERTa-v3-base-
 To use the model for inference:
 
 ```python
-import torch
 from transformers import AutoModelForTokenClassification, AutoTokenizer
 
 # Load the model and tokenizer
-model_path = "jordigonzm/mdeberta-v3-base-multilingual-ner"
+model_path = ""jordigonzm/mdeberta-v3-base-multilingual-ner
 model = AutoModelForTokenClassification.from_pretrained(model_path)
 tokenizer = AutoTokenizer.from_pretrained(model_path)
-model.eval()
 
 # NER Prediction Function
 def predict_ner(text):
     tokens = tokenizer(text, truncation=True, padding=True, return_tensors="pt")
-    with torch.no_grad():
-        outputs = model(**tokens)
-    logits = outputs.logits
-    predictions = torch.argmax(logits, dim=-1).squeeze().tolist()
+    outputs = model(**tokens)
+    predictions = outputs.logits.argmax(dim=-1).squeeze().tolist()
     tokens_decoded = tokenizer.convert_ids_to_tokens(tokens["input_ids"].squeeze().tolist())
     return list(zip(tokens_decoded, predictions))