Updated Readme.md

README.md

@@ -1,22 +1,106 @@
 ---
 base_model: unsloth/phi-4-unsloth-bnb-4bit
 tags:
-- text-generation-inference
-- transformers
-- unsloth
-- llama
-- trl
+  - text-generation
+  - transformers
+  - unsloth
+  - llama
+  - trl
 license: apache-2.0
 language:
-- en
+  - en
 ---
 
-# Uploaded  model
+# 🧮 Phi-4 Math Reasoning Model (LoRA Finetuned)
 
-- **Developed by:** RobinMillford
-- **License:** apache-2.0
-- **Finetuned from model :** unsloth/phi-4-unsloth-bnb-4bit
+## 📌 Model Overview
+This model is a **LoRA fine-tuned version** of [unsloth/phi-4-unsloth-bnb-4bit](https://huggingface.co/unsloth/phi-4-unsloth-bnb-4bit).  
+It has been fine-tuned specifically for **math reasoning tasks**, capable of solving step-by-step arithmetic, algebra, and logic problems.  
 
-This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+The base model is **Phi-4**, a 14B-parameter LLaMA variant optimized with [Unsloth](https://github.com/unslothai/unsloth) for **2x faster training** using Hugging Face’s [TRL](https://huggingface.co/docs/trl) library.  
+This version uses **bnb-4bit quantization**, making it memory efficient and suitable for single-GPU setups such as **Tesla T4 (16GB)** or consumer GPUs.
 
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+---
+
+## ⚡ Key Features
+- 🧠 Fine-tuned for **math reasoning and step-by-step solutions**  
+- ⚡ Efficient: 4-bit quantized, runs on **a single GPU** or even CPU (slower)  
+- 🚀 Trained with **Unsloth + TRL** for fast and memory-efficient fine-tuning  
+- 📚 Based on **Phi-4 (14B LLaMA model)**  
+
+---
+
+## 📥 Installation
+Ensure you have the latest versions of the required libraries:
+```bash
+pip install unsloth transformers accelerate bitsandbytes
+```
+
+
+
+🖥️ Usage (Colab / Local GPU)
+
+```bash
+import torch
+from unsloth import FastLanguageModel
+from transformers import TextStreamer
+
+# Load the LoRA fine-tuned model
+model_name = "RobinMillford/phi-4-math-reasoning-lora"
+model, tokenizer = FastLanguageModel.from_pretrained(
+    model_name=model_name,
+    max_seq_length=2048,
+    dtype=torch.float16,   # fp16 recommended for GPU
+    load_in_4bit=True,     # load in 4-bit quantized mode
+    device_map="auto"      # automatically place layers on GPU/CPU
+)
+
+# Prepare for inference
+FastLanguageModel.for_inference(model)
+
+# Example: Generate a step-by-step solution
+streamer = TextStreamer(tokenizer)
+inputs = tokenizer(
+    "Solve step by step: Q: What is 24 * 17 ? A:",
+    return_tensors="pt"
+).to("cuda")
+
+_ = model.generate(**inputs, streamer=streamer, max_new_tokens=500)
+```
+
+
+
+📊 Example Output
+
+Prompt:
+
+Solve step by step: Q: What is 45 + 67 ?
+
+
+
+Response:
+
+Step 1: Add the ones digits: 5 + 7 = 12. Write down 2 and carry over 1.
+Step 2: Add the tens digits plus carry: 4 + 6 + 1 = 11.
+Step 3: Combine the results: 112.
+Answer: 112
+
+
+
+
+⚠️ Disclaimer
+
+
+This model is intended for research and educational purposes only.
+
+It may not be fully accurate for complex math reasoning tasks. Always verify critical calculations independently.
+
+
+
+## ❤️ Made With
+- [Unsloth](https://github.com/unslothai/unsloth)  
+- [Transformers](https://huggingface.co/docs/transformers)  
+- [TRL](https://huggingface.co/docs/trl)  
+- [Kaggle Notebook](https://www.kaggle.com/code/yaminh/finetuning-a-llm-for-math-reasoning-sbs)
+
+---