Update README.md

README.md

@@ -52,3 +52,96 @@ To download Original checkpoints, see the example command below leveraging `hugg
 ```
 huggingface-cli download prithivMLmods/Llama-Thinker-3B-Preview --include "original/*" --local-dir Llama-Thinker-3B-Preview
 ```
+
+Here’s a version tailored for the **Llama-Thinker-3B-Preview-GGUF** model:
+
+---
+
+# **How to Run Llama-Thinker-3B-Preview on Ollama Locally**
+
+This guide demonstrates how to run the **Llama-Thinker-3B-Preview-GGUF** model locally using Ollama. The model is instruction-tuned for multilingual tasks and complex reasoning, making it highly versatile for a wide range of use cases. By the end, you'll be equipped to run this and other open-source models with ease.
+
+---
+
+## Example 1: How to Run the Llama-Thinker-3B-Preview Model
+
+The **Llama-Thinker-3B** model is a pretrained and instruction-tuned LLM, designed for complex reasoning tasks across multiple languages. In this guide, we'll interact with it locally using Ollama, with support for quantized models.
+
+### Step 1: Download the Model
+
+First, download the **Llama-Thinker-3B-Preview-GGUF** model using the following command:
+
+```bash
+ollama run llama-thinker-3b-preview.gguf
+```
+
+### Step 2: Model Initialization and Download
+
+Once the command is executed, Ollama will initialize and download the necessary model files. You should see output similar to this:
+
+```plaintext
+pulling manifest
+pulling a12cd3456efg... 100% ▕██████████████████████████████████████████████████████████████████████████████████████████▏ 3.2 GB
+pulling 9f87ghijklmn... 100% ▕██████████████████████████████████████████████████████████████████████████████████████████▏ 6.5 KB
+verifying sha256 digest
+writing manifest
+removing any unused layers
+success
+>>> Send a message (/? for help)
+```
+
+### Step 3: Interact with the Model
+
+Once the model is fully loaded, you can interact with it by sending prompts. For example, let's ask:
+
+```plaintext
+>>> How can you assist me today?
+```
+
+A sample response might look like this [may / maynot be identical]:
+
+```plaintext
+I am Llama-Thinker-3B, an advanced AI language model designed to assist with complex reasoning, multilingual tasks, and general-purpose queries. Here are a few things I can help you with:
+
+1. Answering complex questions in multiple languages.
+2. Assisting with creative writing, content generation, and problem-solving.
+3. Providing detailed summaries and explanations.
+4. Translating text across different languages.
+5. Generating ideas for personal or professional use.
+6. Offering insights on technical topics.
+
+Feel free to ask me anything you'd like assistance with!
+```
+
+### Step 4: Exit the Program
+
+To exit the program, simply type:
+
+```plaintext
+/exit
+```
+
+---
+
+## Example 2: Using Multi-Modal Models (Future Use)
+
+In the future, Ollama may support multi-modal models where you can input both text and images for advanced interactions. This section will be updated as new capabilities become available.
+
+---
+
+## Notes on Using Quantized Models
+
+Quantized models like **llama-thinker-3b-preview.gguf** are optimized for efficient performance on local systems with limited resources. Here are some key points to ensure smooth operation:
+
+1. **VRAM/CPU Requirements**: Ensure your system has adequate VRAM or CPU resources to handle model inference.
+2. **Model Format**: Use the `.gguf` model format for compatibility with Ollama.
+
+---
+
+# **Conclusion**
+
+Running the **Llama-Thinker-3B-Preview** model locally using Ollama provides a powerful way to leverage open-source LLMs for complex reasoning and multilingual tasks. By following this guide, you can explore other models and expand your use cases as new models become available.
+
+--- 
+
+Let me know if you’d like further customizations!