Update README.md

README.md

@@ -1,22 +1,262 @@
 ---
-base_model: unsloth/deepseek-r1-distill-llama-8b-unsloth-bnb-4bit
+base_model: unsloth/DeepSeek-R1-Distill-Llama-8B  
 tags:
 - text-generation-inference
 - transformers
 - unsloth
 - llama
-- trl
-license: apache-2.0
+- gguf
+- ollama  
+license: apache-2.0  
 language:
 - en
+
 ---
 
-# Testing The Reasoning Model...
+# Kubernetes Assistant Model (8B)
 
 - **Developed by:** dereklck
-- **License:** apache-2.0
-- **Finetuned from model :** unsloth/deepseek-r1-distill-llama-8b-unsloth-bnb-4bit
+- **License:** Apache-2.0
+- **Fine-tuned from model:** [unsloth/DeepSeek-R1-Distill-Llama-8B](https://huggingface.co/unsloth/DeepSeek-R1-Distill-Llama-8B)
+- **Model type:** GGUF (compatible with Ollama)
+- **Language:** English
+
+This Llama-based model was fine-tuned to assist users with Kubernetes commands and questions. It has three primary features:
+
+1. **Generating accurate `kubectl` commands** based on user instructions.
+2. **Providing concise explanations about Kubernetes** for general queries.
+3. **Politely requesting additional information** if the instruction is incomplete or ambiguous.
+
+**Update:** The **8B model** provides improved accuracy and reliability compared to previous versions, including better adherence to guidelines and reduced hallucinations. Users can expect more precise responses when interacting with this model.
+
+The model was trained efficiently using [Unsloth](https://github.com/unslothai/unsloth) and Hugging Face's TRL library.
+
+---
+
+## How to Use the Model
+
+This section provides instructions on how to run the model using Ollama and the provided Modelfile.
+
+### Prerequisites
+
+- Install [Ollama](https://github.com/jmorganca/ollama) on your system.
+- Ensure you have access to the model hosted on Hugging Face: `hf.co/dereklck/kubernetes_operator_8b_deepseek_peft_gguf`.
+
+### Steps
+
+1. **Create the Modelfile**
+
+   Save the following content as a file named `Modelfile`:
+
+   ```plaintext
+   FROM hf.co/dereklck/kubernetes_operator_8b_deepseek_peft_gguf
+
+   PARAMETER temperature 0.3
+   PARAMETER stop "</s>"
+
+   TEMPLATE """
+   You are an AI assistant that helps users with Kubernetes commands and questions.
+
+   **IMPORTANT: Strictly follow the guidelines below. Do not deviate under any circumstances.**
+
+   ---
+
+   ### **Your Behavior Guidelines:**
+
+   #### **1. For clear and complete instructions:**
+
+   - **Provide ONLY** the exact `kubectl` command needed to fulfill the user's request.
+   - **DO NOT** include extra explanations, placeholders (like `<pod_name>`, `my-pod`), example values, or context.
+   - **Enclose the command within a code block** using `bash` syntax highlighting.
+
+   #### **2. For incomplete or ambiguous instructions:**
+
+   - **Politely ask** the user for the specific missing information **in one sentence**.
+   - **DO NOT** provide any commands, examples, or placeholders in your response.
+   - **Respond in plain text**, clearly stating what information is needed.
+   - **DO NOT** include any additional information or text beyond the question.
+
+   #### **3. For general Kubernetes questions:**
+
+   - **Provide a concise and accurate explanation**.
+   - **DO NOT** include any commands unless specifically requested.
+   - **Ensure that the explanation fully addresses the user's question without irrelevant information.
+
+   ---
+
+   ### **IMPORTANT RULES (READ CAREFULLY):**
+
+   - **DO NOT generate CLI commands containing placeholders or example values** (e.g., `<pod_name>`, `my-pod`, `your-pod`).
+   - **DO NOT invent resource names or use generic names**. If the resource name is not provided, ask for it.
+   - **Always ensure CLI commands are complete, valid, and executable AS IS**.
+   - **If user input is insufficient to form a complete command, ASK FOR CLARIFICATION** instead of using placeholders or examples.
+   - **DO NOT output any additional text beyond what's necessary**.
+
+   ---
+
+   ### Instruction:
+   {{ .Prompt }}
+
+   ### Response:
+   """
+
+   ```
+
+2. **Create the Model with Ollama**
+
+   Open your terminal and run the following command to create the model:
+
+   ```bash
+   ollama create kubernetes_assistant_8b -f Modelfile
+   ```
+
+   This command tells Ollama to create a new model named `kubernetes_assistant_8b` using the configuration specified in `Modelfile`.
+
+3. **Run the Model**
+
+   Start interacting with your model:
+
+   ```bash
+   ollama run kubernetes_assistant_8b
+   ```
+
+   This will initiate the model and prompt you for input based on the template provided.
+
+   Alternatively, you can provide an instruction directly:
+
+   ```bash
+   ollama run kubernetes_assistant_8b -p "Create a namespace called 'production'."
+   ```
+
+   **Example Output:**
+
+   ```bash
+   kubectl create namespace production
+   ```
+
+---
+
+## Model Details
+
+### Purpose
+
+The model assists users by:
+
+- **Generating accurate `kubectl` commands** based on natural language instructions.
+- **Providing concise explanations about Kubernetes** for general queries.
+- **Politely requesting additional information** if the instruction is incomplete or ambiguous.
+
+### Intended Users
+
+- Kubernetes administrators
+- DevOps engineers
+- Developers working with Kubernetes clusters
+
+### Training Process
+
+- **Base Model:** Unsloth's DeepSeek-R1-Distill-Llama-8B
+- **Fine-tuning:** Leveraged the Unsloth framework and Hugging Face's TRL library for efficient training.
+- **Training Data:** Customized dataset focused on Kubernetes operations, including:
+  - **`kubectl` Command Generation:** Commands for various Kubernetes tasks.
+  - **Clarification Requests:** Responses requesting specific information when instructions are incomplete.
+  - **Explanations:** Concise explanations of Kubernetes concepts.
+  - The dataset contains approximately 1,500 entries.
+
+---
+
+## Model Features
+
+### 1. Command Generation in Bash Format
+
+When the model generates CLI commands, it provides them in `bash` format, enclosed within code blocks for easy execution and clarity. This allows users to copy and paste the commands directly into their terminal.
+
+### 2. Handling Ambiguity with Polite Clarifications
+
+If the instruction is incomplete or ambiguous, the model will politely ask for the specific missing information instead of making assumptions. This ensures accuracy and prevents the execution of incorrect commands.
+
+### 3. Providing Concise Explanations
+
+For general Kubernetes questions, the model offers concise and accurate explanations without unnecessary details, helping users understand concepts quickly.
+
+### 4. Enhanced Accuracy with 8B Model
+
+The transition to the 8B model has significantly **improved accuracy and reduced hallucinations** compared to smaller models. The 8B model provides more precise and reliable responses, enhancing the overall user experience.
+
+---
+
+## Examples
+
+### Example 1: Generating a Command
+
+**Instruction:**
+
+```
+Get the list of all pods in the 'staging' namespace.
+```
+
+**Response:**
+
+```bash
+kubectl get pods -n staging
+```
+
+---
+
+### Example 2: Handling Ambiguity
+
+**Instruction:**
+
+```
+Delete the deployment.
+```
+
+**Response:**
+
+```
+Please specify the name of the deployment you wish to delete.
+```
+
+---
+
+### Example 3: Providing Explanations
+
+**Instruction:**
+
+```
+What is a StatefulSet in Kubernetes?
+```
+
+**Response:**
+
+```
+A StatefulSet manages the deployment and scaling of a set of pods, providing guarantees about the ordering and uniqueness of those pods. It's commonly used for stateful applications requiring stable network identities and persistent storage.
+```
+
+---
+
+## Limitations and Considerations
+
+- **Accuracy:** While the 8B model significantly improves accuracy, the model may occasionally produce incorrect or suboptimal commands. Always review the output before execution.
+- **Resource Requirements:** The 8B model may require more computational resources compared to smaller models. Ensure your environment meets the necessary requirements for smooth operation.
+- **Security:** Be cautious when executing generated commands, especially in production environments.
+
+---
+
+## Feedback and Contributions
+
+We welcome any comments or participation to improve the model and dataset. If you encounter issues or have suggestions for improvement:
+
+- **GitHub:** [Unsloth Repository](https://github.com/unslothai/unsloth)
+- **Contact:** Reach out to the developer, **dereklck**, for further assistance.
+
+---
+
+**Note:** This model provides assistance in generating Kubernetes commands and explanations based on user input. Always verify the generated commands in a safe environment before executing them in a production cluster.
+
+---
+
+## Summary
 
-This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+The **Kubernetes Assistant Model (8B)** is a powerful tool designed to help users interact with Kubernetes clusters more efficiently. By leveraging advanced language modeling techniques, the model provides accurate `kubectl` commands, helpful explanations, and polite clarifications when necessary. The use of the 8B model enhances the precision and reliability of responses, making it a valuable asset for anyone working with Kubernetes.
 
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+---