Update README.md

README.md

@@ -1,9 +1,10 @@
 ---
-base_model: unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit
+base_model:
+- meta-llama/Llama-3.2-3B-Instruct
 tags:
 - text-generation-inference
 - transformers
-- unsloth
+- Reasoning
 - llama
 - gguf
 license: apache-2.0
@@ -15,8 +16,6 @@ language:
 
 - **Developed by:** johnnietien
 - **License:** apache-2.0
-- **Finetuned from model :** unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit
+- **Finetuned from model :** meta-llama/Llama-3.2-3B-Instruct
 
-This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
-
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+This is one of my first Reasoning model can have an “aha moment” same as DeepSeek’s R1. We've enhanced the entire GRPO process, making it use 80% less VRAM than Hugging Face + FA2. This allows you to reproduce R1-Zero's "aha moment" on just 7GB of VRAM using llama-3.2-3b. Please note, this isn’t fine-tuning DeepSeek’s R1 distilled models or using distilled data from R1 for tuning. This is converting a standard model into a full-fledged reasoning model using GRPO.