Update README.md

README.md

@@ -62,22 +62,4 @@ The following hyperparameters were used during training:
 - Transformers 4.35.0
 - Pytorch 2.1.0
 - Datasets 2.14.6
-- Tokenizers 0.14.1
-
-## Inference API
-이 섹션에서는 `bert-base-uncased` 모델을 사용하여 텍스트 분류 작업을 수행하는 방법을 보여주는 예제 코드를 변경할 수 있습니다.
-
-```python
-from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline
-
-model_name = "CDRI-Eddy/ingredients_classification_model"
-model = AutoModelForSequenceClassification.from_pretrained(model_name)
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-
-nlp = pipeline("text-classification", model=model, tokenizer=tokenizer)
-
-# 예제 입력 문장 변경
-input_sentence = "Here is the sentence you want the model to classify."
-result = nlp(input_sentence)
-
-print(result)
+- Tokenizers 0.14.1