Update README.md

README.md

@@ -1,43 +1,51 @@
+---
+license: mit
+
 ---
 license: mit
 tags:
-  - lora
   - tinyllama
+  - lora
   - cli
   - fine-tuning
   - qna
-  - huggingface
-model_name: cli-lora-tinyllama
-base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
-datasets:
-  - custom-cli-qa
+  - transformers
+  - peft
 library_name: transformers
-pipeline_tag: text-generation
+datasets:
+  - custom
+language: en
+model_type: causal-lm
 ---
 
-# CLI LoRA-TinyLlama
+# 🔧 CLI LoRA-TinyLlama
 
-Fine-tuned version of [TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) on a custom dataset of CLI-related Q&A using LoRA (Low-Rank Adaptation).
+A fine-tuned version of [TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) on a custom dataset of command-line Q&A, using **LoRA** (Low-Rank Adaptation). Built for fast, accurate help on common CLI topics.
 
 ---
 
-## Base Model
-- **Model**: `TinyLlama/TinyLlama-1.1B-Chat-v1.0`
-- **Technique**: Fine-tuning using [LoRA](https://arxiv.org/abs/2106.09685)
-- **Libraries**: `transformers`, `peft`, `datasets`, `accelerate`
+## 🧩 Base Model
+
+- Model: `TinyLlama/TinyLlama-1.1B-Chat-v1.0`
+- Fine-Tuning Method: [LoRA](https://arxiv.org/abs/2106.09685)
+- Libraries Used: `transformers`, `peft`, `datasets`, `accelerate`
 
 ---
 
-## Dataset
-- Custom-made with **150+ Q&A** pairs on:
+## 📚 Dataset
+
+- Custom dataset with **150+ Q&A pairs** covering:
   - `git`, `bash`, `grep`, `tar`, `venv`
-- Stored in: `cli_questions.json`
+- Raw file: `cli_questions.json`
 - Tokenized version: `tokenized_dataset/`
 
 ---
 
-## Fine-Tuning Configuration
+## 🛠️ Training Configuration
+
 ```python
+from peft import LoraConfig
+
 base_model = "TinyLlama/TinyLlama-1.1B-Chat-v1.0"
 
 lora_config = LoraConfig(