Update README.md

README.md

@@ -13,12 +13,38 @@ datasets:
 - bespokelabs/Bespoke-Stratos-17k
 ---
 
-# Uploaded  model
+# Phi4 Turn R1Distill LoRA Adapters
 
-- **Developed by:** Quazim0t0
-- **License:** apache-2.0
-- **Finetuned from model :** unsloth/phi-4-unsloth-bnb-4bit
+## Overview
+Hey! These LoRA adapters are trained using different reasoning datasets that utilize **Thought** and **Solution** for reasoning responses.  
+I hope these help jumpstart your project! These adapters have been trained on an **A800 GPU** and should provide a solid base for fine-tuning or merging.  
 
-This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+Everything on my page is left **public** for Open Source use.  
 
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+## Available LoRA Adapters  
+Here are the links to the available 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)  
+
+## Usage  
+These adapters can be loaded and used with `peft` and `transformers`. Here’s a quick example:
+
+```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()