Update README.md

README.md

@@ -141,6 +141,8 @@ model-index:
 
 This is the [flan-t5-base](https://huggingface.co/google/flan-t5-base) model, fine-tuned using the [SQuAD2.0](https://huggingface.co/datasets/squad_v2) dataset. It's been trained on question-answer pairs, including unanswerable questions, for the task of Extractive Question Answering.
 
+**UPDATE:** With transformers version 4.31.0 the `use_remote_code=True` is no longer necessary and will cause `AutoModelForQuestionAnswering.from_pretrained()` to fail.
+
 **NOTE:** The `<cls>` token must be manually added to the beginning of the question for this model to work properly.
 It uses the `<cls>` token to be able to make "no answer" predictions.
 The t5 tokenizer does not automatically add this special token which is why it is added manually.
@@ -168,7 +170,7 @@ nlp = pipeline(
   'question-answering',
   model=model_name,
   tokenizer=model_name,
-  trust_remote_code=True,
+  # trust_remote_code=True, # Do not use if version transformers>=4.31.0
 )
 qa_input = {
 'question': f'{nlp.tokenizer.cls_token}Where do I live?',  # '<cls>Where do I live?'
@@ -179,7 +181,8 @@ res = nlp(qa_input)
 
 # b) Load model & tokenizer
 model = AutoModelForQuestionAnswering.from_pretrained(
-  model_name, trust_remote_code=True
+  model_name,
+  # trust_remote_code=True # Do not use if version transformers>=4.31.0
 )
 tokenizer = AutoTokenizer.from_pretrained(model_name)