Update README.md

README.md

@@ -49,12 +49,12 @@ def predict_NuExtract(model, tokenizer, texts, template, batch_size=1, max_lengt
     
     outputs = []
     with torch.no_grad():
-		    for i in range(0, len(prompts), batch_size):
-				    batch_prompts = prompts[i:i+batch_size]
-				    batch_encodings = tokenizer(batch_prompts, return_tensors="pt", truncation=True, padding=True, max_length=max_length).to(model.device)
-    
-				    pred_ids = model.generate(**batch_encodings, max_new_tokens=max_new_tokens)
-				    outputs += tokenizer.batch_decode(pred_ids, skip_special_tokens=True)
+        for i in range(0, len(prompts), batch_size):
+            batch_prompts = prompts[i:i+batch_size]
+            batch_encodings = tokenizer(batch_prompts, return_tensors="pt", truncation=True, padding=True, max_length=max_length).to(model.device)
+
+            pred_ids = model.generate(**batch_encodings, max_new_tokens=max_new_tokens)
+            outputs += tokenizer.batch_decode(pred_ids, skip_special_tokens=True)
 
     return [output.split("<|output|>")[1] for output in outputs]