Update README.md

README.md

@@ -50,7 +50,9 @@ pipeline_tag: text-generation
 
 ---
 
-## 🚀 Quick Start
+## Running with the ```pipeline``` API
+
+You can initialize the model and processor for inference with ```pipeline``` as follows.
 
 ```python
 from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
@@ -64,4 +66,14 @@ pipe = pipeline("text-classification", model=model, tokenizer=tokenizer)
 
 text = "무료 쿠폰 지급! 지금 바로 클릭하세요 👉 https://spam.link 해당 문자 스팸인가요?" 
 result = pipe(text, top_k=2)
-print(result)
+print(result)
+```
+
+## Quick Start
+
+Training was conducted using the Axolotl framework, a flexible and efficient fine-tuning system designed for large language models.
+
+Axolotl enables seamless configuration and execution of full fine-tuning, LoRA, and DPO pipelines through simple YAML-based workflows.
+It integrates with PyTorch and Hugging Face Transformers, supporting distributed strategies such as FSDP and DeepSpeed for optimized performance on multi-GPU environments.
+
+This framework streamlines experimentation and scaling by allowing researchers to define training parameters, datasets, and model behaviors declaratively — reducing boilerplate and ensuring reproducible results across setups.