Update README.md

README.md

@@ -8,7 +8,7 @@ pipeline_tag: question-answering
 
 <!-- Provide a quick summary of what the model is/does. -->
 
-This model is fine-tuned with LLaMA-2 with 8 Nvidia A100-80G GPUs using 3,000,000 groups of conversations in the context of mathematics by students and facilitators on Algebra Nation (https://www.mathnation.com/). Llama-2-Qlora consists of 32 layers and over 7 billion parameters, consuming up to 13.5 gigabytes of disk space. Researchers can experiment with and finetune the model to help construct math conversational AI that can effectively respond generation in a mathematical context.
+This model is fine-tuned with LLaMA-2 with 8 Nvidia A100-80G GPUs using 3,000,000 groups of conversations in the context of mathematics by students and facilitators on Algebra Nation (https://www.mathnation.com/). Llama-2-Qlora consists of 32 layers and over 7 billion parameters, consuming up to 13.5 gigabytes of disk space. Researchers can experiment with and finetune the model to help construct dedicated LLMs for downstream tasks (e.g., classification) related to K-12 math learning.
 ### Here is how to use it with texts in HuggingFace
 ```python
 import torch