Update README.md

README.md

@@ -1,35 +1,46 @@
-# Fine-Tuned LLaMA 3.2 1B – Weekly & Daily Task Planner
+---
+license: apache-2.0
+tags:
+  - causal-lm
+  - llama
+  - peft
+  - lora
+  - fine-tuning
+  - text-generation
+  - productivity
+library_name: transformers
+---
+
+# Daily Tasks Fine Tuned LLaMA 3.2 1B – Weekly & Daily Task Planner
 
 ## Model Description
-This is a **fine-tuned LLaMA 3.2 1B Instruct model** for generating structured weekly and daily plans. 
-It can produce:
+This is a **fine-tuned LLaMA 3.2 1B model** designed to generate structured weekly and daily plans. It can produce:
 
 - Workout routines
 - Study schedules
 - Meal plans
 - Other daily task setups
 
-Fine-tuning was done using **PEFT LoRA** in **float16** to reduce memory usage.
+Fine-tuning was done using **PEFT LoRA** with float16 precision for efficient training on GPU.
 
 ---
 
 ## Intended Use
-This model is intended for **personal productivity planning, fitness scheduling, and educational planning**. 
-It is **not meant for medical or critical decision-making**.
+This model is intended for **personal productivity, fitness planning, and educational scheduling**. It is **not meant for medical, legal, or critical decision-making**.
 
 ---
 
-## How to Use
+## Usage
 
 ```python
 from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
 
-model_name = "your-username/fine-tuned-llama3-2-1b"
+model_name = "your-username/daily_tasks_fine_tuned_llama3_2_1b"
 
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = AutoModelForCausalLM.from_pretrained(model_name)
 
-pipe = pipeline(
+generator = pipeline(
     "text-generation",
     model=model,
     tokenizer=tokenizer,
@@ -37,5 +48,5 @@ pipe = pipeline(
 )
 
 prompt = "Plan a 7-day workout routine for cardiovascular health."
-output = pipe(prompt, max_new_tokens=600)
+output = generator(prompt, max_new_tokens=600)
 print(output[0]['generated_text'])