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--- |
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base_model: unsloth/DeepSeek-R1-Distill-Llama-8B |
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tags: |
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- text-generation-inference |
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- transformers |
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- unsloth |
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- llama |
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- gguf |
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- ollama |
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license: apache-2.0 |
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language: |
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- en |
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--- |
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➕ YAML Creation Feature will be added |
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# Kubernetes Assistant Model (8B) |
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- **Developed by:** dereklck |
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- **License:** Apache-2.0 |
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- **Fine-tuned from model:** [unsloth/DeepSeek-R1-Distill-Llama-8B](https://huggingface.co./unsloth/DeepSeek-R1-Distill-Llama-8B) |
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- **Model type:** GGUF (compatible with Ollama) |
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- **Language:** English |
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This Llama-based model was fine-tuned to assist users with Kubernetes commands and questions. It has three primary features: |
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1. **Generating accurate `kubectl` commands** based on user instructions. |
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2. **Providing concise explanations about Kubernetes** for general queries. |
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3. **Politely requesting additional information** if the instruction is incomplete or ambiguous. |
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**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. |
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The model was trained efficiently using [Unsloth](https://github.com/unslothai/unsloth) and Hugging Face's TRL library. |
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--- |
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## How to Use the Model |
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This section provides instructions on how to run the model using Ollama and the provided Modelfile. |
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### Prerequisites |
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- Install [Ollama](https://github.com/jmorganca/ollama) on your system. |
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- Ensure you have access to the model hosted on Hugging Face: `hf.co/dereklck/kubernetes_operator_8b_deepseek_peft_gguf`. |
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### Steps |
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1. **Create the Modelfile** |
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Save the following content as a file named `Modelfile`: |
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```plaintext |
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FROM hf.co/dereklck/kubernetes_operator_8b_deepseek_peft_gguf |
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PARAMETER temperature 0.3 |
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PARAMETER stop "</s>" |
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TEMPLATE """ |
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You are an AI assistant that helps users with Kubernetes commands and questions. |
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**IMPORTANT: Strictly follow the guidelines below. Do not deviate under any circumstances.** |
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--- |
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### **Your Behavior Guidelines:** |
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#### **1. For clear and complete instructions:** |
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- **Provide ONLY** the exact `kubectl` command needed to fulfill the user's request. |
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- **DO NOT** include extra explanations, placeholders (like `<pod_name>`, `my-pod`), example values, or context. |
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- **Enclose the command within a code block** using `bash` syntax highlighting. |
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#### **2. For incomplete or ambiguous instructions:** |
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- **Politely ask** the user for the specific missing information **in one sentence**. |
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- **DO NOT** provide any commands, examples, or placeholders in your response. |
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- **Respond in plain text**, clearly stating what information is needed. |
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- **DO NOT** include any additional information or text beyond the question. |
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#### **3. For general Kubernetes questions:** |
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- **Provide a concise and accurate explanation**. |
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- **DO NOT** include any commands unless specifically requested. |
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- **Ensure that the explanation fully addresses the user's question without irrelevant information. |
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--- |
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### **IMPORTANT RULES (READ CAREFULLY):** |
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- **DO NOT generate CLI commands containing placeholders or example values** (e.g., `<pod_name>`, `my-pod`, `your-pod`). |
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- **DO NOT invent resource names or use generic names**. If the resource name is not provided, ask for it. |
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- **Always ensure CLI commands are complete, valid, and executable AS IS**. |
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- **If user input is insufficient to form a complete command, ASK FOR CLARIFICATION** instead of using placeholders or examples. |
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- **DO NOT output any additional text beyond what's necessary**. |
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--- |
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### Instruction: |
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{{ .Prompt }} |
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### Response: |
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""" |
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``` |
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2. **Create the Model with Ollama** |
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Open your terminal and run the following command to create the model: |
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```bash |
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ollama create kubernetes_assistant_8b -f Modelfile |
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``` |
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This command tells Ollama to create a new model named `kubernetes_assistant_8b` using the configuration specified in `Modelfile`. |
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3. **Run the Model** |
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Start interacting with your model: |
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```bash |
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ollama run kubernetes_assistant_8b |
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``` |
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This will initiate the model and prompt you for input based on the template provided. |
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Alternatively, you can provide an instruction directly: |
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```bash |
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ollama run kubernetes_assistant_8b -p "Create a namespace called 'production'." |
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``` |
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**Example Output:** |
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```bash |
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kubectl create namespace production |
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``` |
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--- |
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## Model Details |
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### Purpose |
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The model assists users by: |
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- **Generating accurate `kubectl` commands** based on natural language instructions. |
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- **Providing concise explanations about Kubernetes** for general queries. |
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- **Politely requesting additional information** if the instruction is incomplete or ambiguous. |
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### Intended Users |
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- Kubernetes administrators |
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- DevOps engineers |
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- Developers working with Kubernetes clusters |
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### Training Process |
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- **Base Model:** Unsloth's DeepSeek-R1-Distill-Llama-8B |
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- **Fine-tuning:** Leveraged the Unsloth framework and Hugging Face's TRL library for efficient training. |
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- **Training Data:** Customized dataset focused on Kubernetes operations, including: |
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- **`kubectl` Command Generation:** Commands for various Kubernetes tasks. |
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- **Clarification Requests:** Responses requesting specific information when instructions are incomplete. |
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- **Explanations:** Concise explanations of Kubernetes concepts. |
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- The dataset contains approximately 1,500 entries. |
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--- |
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## Model Features |
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### 1. Command Generation in Bash Format |
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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. |
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### 2. Handling Ambiguity with Polite Clarifications |
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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. |
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### 3. Providing Concise Explanations |
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For general Kubernetes questions, the model offers concise and accurate explanations without unnecessary details, helping users understand concepts quickly. |
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### 4. Enhanced Accuracy with 8B Model |
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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. |
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--- |
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## Examples |
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### Example 1: Generating a Command |
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**Instruction:** |
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``` |
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Get the list of all pods in the 'staging' namespace. |
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``` |
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**Response:** |
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```bash |
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kubectl get pods -n staging |
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``` |
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--- |
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### Example 2: Handling Ambiguity |
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**Instruction:** |
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``` |
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Delete the deployment. |
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``` |
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**Response:** |
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``` |
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Please specify the name of the deployment you wish to delete. |
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``` |
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--- |
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### Example 3: Providing Explanations |
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**Instruction:** |
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``` |
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What is a StatefulSet in Kubernetes? |
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``` |
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**Response:** |
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``` |
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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. |
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``` |
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--- |
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## Limitations and Considerations |
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- **Accuracy:** While the 8B model significantly improves accuracy, the model may occasionally produce incorrect or suboptimal commands. Always review the output before execution. |
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- **Resource Requirements:** The 8B model may require more computational resources compared to smaller models. Ensure your environment meets the necessary requirements for smooth operation. |
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- **Security:** Be cautious when executing generated commands, especially in production environments. |
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## Feedback and Contributions |
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We welcome any comments or participation to improve the model and dataset. If you encounter issues or have suggestions for improvement: |
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- **GitHub:** [Unsloth Repository](https://github.com/unslothai/unsloth) |
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- **Contact:** Reach out to the developer, **dereklck**, for further assistance. |
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**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. |
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--- |
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## Summary |
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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. |
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--- |
