Update README.md

README.md

@@ -9,7 +9,7 @@ datasets:
 # FinePDFs-OCR-Quality classifier (English)
 
 ## Model summary
-This is a classifier for judging the educational value of web pages. It was developed to filter and curate educational content from web datasets and was trained on 1304547
+This is a classifier for judging the ocr quality value of web pages. It was developed to filter and curate well extracted content from web datasets and was trained on 1304547
  [annotations](https://huggingface.co/datasets/HuggingFaceFW/finepdfs_eng_Latn_labeled) generated by [Qwen3-235B-A22B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-235B-A22B-Instruct-2507) for web samples from [FinePDFs](https://huggingface.co/datasets/HuggingFaceFW/finepdfs) dataset.
 
 ### How to use in transformers
@@ -21,8 +21,8 @@ import re
 CHUNK_SIZE = 2048 - 2
 MAX_CHARS = 10_000
 
-tokenizer = AutoTokenizer.from_pretrained("HuggingFaceFW/finepdfs_edu_classifier_English")
-model = AutoModelForSequenceClassification.from_pretrained("HuggingFaceFW/finepdfs_edu_classifier_English")
+tokenizer = AutoTokenizer.from_pretrained("HuggingFaceFW/finepdfs_ocr_quality_classifier_eng_Latn")
+model = AutoModelForSequenceClassification.from_pretrained("HuggingFaceFW/finepdfs_ocr_quality_classifier_eng_Latn")
 regex_whitespace = re.compile(r'\s')
 
 def create_text_chunks(text: str, tokenizer):