Update README.md

README.md

@@ -10,8 +10,10 @@ inference: false
 
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/60e50ce5350d181892d5a636/mC3xwgJJ139R9LXbXpBWj.png)
 
+## **"Garbage in, garbage out. A language model is only as good as its training data irrespective of its parameter count."**
+
 This educational value classifier is deeply inspired by [Textbooks Are All You Need](https://arxiv.org/abs/2306.11644), where a classifier was developed to predict the educational value of data, and was then used for data filtering.  
-Model is built on fasttext - it can classify more than 2000 examples per second in CPU, and so I can be used **on-the-fly**.  
+Model is built on fasttext - it can classify more than 2000 examples per second in CPU, and so it can be used **on-the-fly** during pretraining.  
 This model can classify if a text has high educational value (more explicitly defined then textbook quality).  This definition change is a substantial change vs [kenhktsui/llm-data-textbook-quality-fasttext-classifer-v1](https://huggingface.co/kenhktsui/llm-data-textbook-quality-fasttext-classifer-v1).   
 It can be used as a filter for data curation when training a LLM.  
 There are 3 labels instead of 2 labels, as it offers higher granularity of educational value.