Update README.md

README.md

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 - **15$ Training...I'm actually amazed by the results.**
 
 
-If using this model for Open WebUI here is a simple function to organize the models responses: https://openwebui.com/f/quaz93/phi4_turn_r1_distill_thought_function_v1
+If using this model for Open WebUI here is a simple function to organize the models responses: https://openwebui.com/f/quaz93/phi4_turn_r1_distill_thought_function_v1
+
+# Phi4 Turn R1Distill LoRA Adapters
+
+## Overview
+These **LoRA adapters** were trained using diverse **reasoning datasets** that incorporate structured **Thought** and **Solution** responses to enhance logical inference. This project was designed to **test the R1 dataset** on **Phi-4**, aiming to create a **lightweight, fast, and efficient reasoning model**.
+
+All adapters were fine-tuned using an **NVIDIA A800 GPU**, ensuring high performance and compatibility for continued training, merging, or direct deployment.  
+As part of an open-source initiative, all resources are made **publicly available** for unrestricted research and development.
+
+---
+
+## LoRA Adapters  
+Below are the currently available LoRA fine-tuned adapters (**as of January 30, 2025**):
+
+- [Phi4.Turn.R1Distill-Lora1](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill-Lora1)  
+- [Phi4.Turn.R1Distill-Lora2](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill-Lora2)  
+- [Phi4.Turn.R1Distill-Lora3](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill-Lora3)  
+- [Phi4.Turn.R1Distill-Lora4](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill-Lora4)  
+- [Phi4.Turn.R1Distill-Lora5](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill-Lora5)  
+- [Phi4.Turn.R1Distill-Lora6](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill-Lora6)  
+- [Phi4.Turn.R1Distill-Lora7](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill-Lora7)  
+- [Phi4.Turn.R1Distill-Lora8](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill-Lora8)  
+
+---
+
+## GGUF Full & Quantized Models  
+To facilitate broader testing and real-world inference, **GGUF Full and Quantized versions** have been provided for evaluation on **Open WebUI** and other LLM interfaces.
+
+### **Version 1**
+- [Phi4.Turn.R1Distill.Q8_0](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill.Q8_0)  
+- [Phi4.Turn.R1Distill.Q4_k](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill.Q4_k)  
+- [Phi4.Turn.R1Distill.16bit](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill.16bit)  
+
+### **Version 1.1**
+- [Phi4.Turn.R1Distill_v1.1_Q4_k](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill_v1.1_Q4_k)  
+
+### **Version 1.2**
+- [Phi4.Turn.R1Distill_v1.2_Q4_k](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill_v1.2_Q4_k)  
+
+### **Version 1.3**
+- [Phi4.Turn.R1Distill_v1.3_Q4_k-GGUF](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill_v1.3_Q4_k-GGUF)  
+
+### **Version 1.4**
+- [Phi4.Turn.R1Distill_v1.4_Q4_k-GGUF](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill_v1.4_Q4_k-GGUF)  
+
+### **Version 1.5**
+- [Phi4.Turn.R1Distill_v1.5_Q4_k-GGUF](https://huggingface.co/Quazim0t0/Phi4.Turn.R1Distill_v1.5_Q4_k-GGUF)  
+
+---
+
+## Usage  
+
+### **Loading LoRA Adapters with `transformers` and `peft`**
+To load and apply the LoRA adapters on Phi-4, use the following approach:
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from peft import PeftModel
+
+base_model = "microsoft/Phi-4"
+lora_adapter = "Quazim0t0/Phi4.Turn.R1Distill-Lora1"
+
+tokenizer = AutoTokenizer.from_pretrained(base_model)
+model = AutoModelForCausalLM.from_pretrained(base_model)
+model = PeftModel.from_pretrained(model, lora_adapter)
+
+model.eval()