Update README.md

README.md

@@ -16,6 +16,29 @@ Llama3-8B-abliterated-Spectrum-slerp is a merge of the following models using [L
 * [yuvraj17/Llama-3-8B-spectrum-25](https://huggingface.co/yuvraj17/Llama-3-8B-spectrum-25)
 * [mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated](https://huggingface.co/mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated)
 
+## Introduction for Model Merging
+
+**Model Merging**, also known as model fusion, is an effective technique that merges the parameters of multiple separate models with different capabilities to build a universal model without needing access to the
+original training data or expensive computation.
+There are bunch of methods, we can use to merge the capabilities of different models (supported by [mergekit](https://github.com/arcee-ai/mergekit)) including:
+
+<figure>
+
+  <img src="https://cdn-uploads.huggingface.co/production/uploads/66137d95e8d2cda230ddcea6/HUflk1elPEom3Pe_vU_Ku.png" width="768" height="768">
+  <figcaption> Merge Methods supported by MergeKit <a href="//github.com/arcee-ai/mergekit?tab=readme-ov-file#merge-methods">Reference</a> </figcaption>
+
+</figure>
+
+For more deep-diving into different merging techniques, visit [Merge Large Language Models with mergekit](https://towardsdatascience.com/merge-large-language-models-with-mergekit-2118fb392b54). 
+
+### Introduction for SLERP Merging
+
+**Spherical Linear Interpolation (SLERP)** is a method used to smoothly interpolate between two vectors. It maintains a constant rate of change and preserves the geometric properties of the spherical space in which the vectors reside. 
+
+SLERP is currently the *most-popular merging method*, preffered over traditional methods because instead of dealing with straight-lines, the interpolation occurs on the surface of a sphere, and it has achieved improved performance to very diverse task.
+> But SLERP is limited to combining only **two models at a time**, although its possible to hierarchically combine multiple models, as shown in [Mistral-7B-Merge-14-v0.1](https://huggingface.co/EmbeddedLLM/Mistral-7B-Merge-14-v0.1).
+
+
 ## 🧩 Configuration
 
 ```yaml
@@ -61,4 +84,12 @@ pipeline = transformers.pipeline(
 
 outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
 print(outputs[0]["generated_text"])
-```
+```
+
+
+## 🏆 Evaluation Results
+Coming soon
+
+## Special thanks & Reference
+- Maxime Labonne for their easy-to-use colab-notebook [Merging LLMs with MergeKit](https://github.com/mlabonne/llm-course/blob/main/Mergekit.ipynb) and [Blog](https://towardsdatascience.com/merge-large-language-models-with-mergekit-2118fb392b54)
+- Authors of [Mergekit](https://github.com/arcee-ai/mergekit)