fix t5 model initalization

README.md

@@ -32,7 +32,10 @@ We recommend to use the model with transformers `ner` pipeline:
 
 ```python
 from transformers import AutoTokenizer, T5PreTrainedModel, T5Config, T5EncoderModel
+from transformers.modeling_outputs import TokenClassifierOutput
+from typing import Union, Optional, Tuple
 from transformers import pipeline
+import torch
 
 class T5EncoderForTokenClassification(T5PreTrainedModel):
     _tied_weights_keys = ["encoder.embed_tokens.weight"]
@@ -155,7 +158,7 @@ def process(text, prompt, treshold=0.5):
 
   return processed_results
 
-tokenizer = AutoTokenizer.from_pretrained("knowledgator/UTC-DeBERTa-base")
+tokenizer = AutoTokenizer.from_pretrained("knowledgator/UTC-T5-large")
 model = T5EncoderForTokenClassification.from_pretrained("knowledgator/UTC-T5-large")
 
 nlp = pipeline("ner", model=model, tokenizer=tokenizer, aggregation_strategy = 'first')