dereklck
/

kubernetes_operator_3b_peft_gguf

@@ -1,290 +1,261 @@
 ---
-base_model: unsloth/Llama-3.2-3B-Instruct-bnb-4bit
 tags:
-  - text-generation-inference
-  - transformers
-  - unsloth
-  - llama
-  - gguf
-  - ollama
-license: apache-2.0
 language:
-  - en
 ---
-# **kubernetes Operator Model - 3B GGUF**
-**Developed by:** dereklck
-**License:** Apache-2.0
-**Fine-tuned from model:** [unsloth/Llama-3.2-3B-Instruct-bnb-4bit](https://huggingface.co/unsloth/Llama-3.2-3B-Instruct-bnb-4bit)
-**Model Type:** GGUF (Quantized format compatible with Ollama)
-**Language:** English
----
-This Llama-based model has been fine-tuned to generate `kubectl` commands based on user descriptions. Leveraging the capabilities of a **3B parameter model**, it offers enhanced understanding and generation abilities compared to its 1B counterpart. The model has been trained efficiently using the [Unsloth](https://github.com/unslothai/unsloth) framework and Hugging Face's TRL library.
-## **📌 Model Details**
-### **🚀 Purpose**
-The model assists users by:
-- **Generating accurate `kubectl` commands** based on natural language descriptions.
-- **Providing concise explanations about Kubernetes** for general queries.
-- **Politely requesting additional information** when the instruction is incomplete or ambiguous.
-### **👥 Intended Users**
-- **Kubernetes Administrators**
-- **DevOps Engineers**
-- **Developers Working with Kubernetes Clusters**
-### **🛠️ Training Process**
-- **Base Model:** Unsloth's Llama-3.2-3B-Instruct-bnb-4bit
-- **Fine-tuning:** Utilized the Unsloth framework and Hugging Face's TRL library for efficient and effective training.
-- **Training Data:** Customized dataset focused on Kubernetes operations and `kubectl` command usage, containing approximately **1,500 entries** for improved coverage.
-### **✨ Key Features**
-#### **1️⃣ Command Generation**
-- **Functionality:** Translates user instructions into executable `kubectl` commands.
-- **Example:**
-  **User:** "Create a namespace called 'production'."
-  **Model Response:**
-  ```bash
-  kubectl create namespace production
-  ```
-#### **2️⃣ Clarification Requests**
-- **Functionality:** Politely asks for more details when the instruction is incomplete.
-- **Example:**
-  **User:** "Show me logs."
-  **Model Response:**
-  "Please specify the name of the pod for which you want to view logs."
-#### **3️⃣ Knowledge Base**
-- **Functionality:** Provides concise and accurate explanations for general Kubernetes concepts.
-- **Example:**
-  **User:** "What is a Deployment in Kubernetes?"
-  **Model Response:**
-  "A Deployment is a Kubernetes resource that manages a replicated application, ensuring that the desired number of pod replicas are running."
-#### **4️⃣ Input Sensitivity**
-- **Functionality:** Recognizes inappropriate language and maintains professionalism.
-- **Example:**
-  **User:** "What the heck is wrong with this cluster?"
-  **Model Response:**
-  "Could you please provide more details about the issue you're experiencing with your cluster?"
----
-## **💻 Usage Instructions**
-### **📝 Prompt Template**
 The model uses the following prompt template to generate responses:
 ```plaintext
 You are an AI assistant that helps users with Kubernetes commands and questions.
-**Guidelines:**
-1. **For clear instructions:**
-   - Provide **only** the exact `kubectl` command needed.
-   - Do **not** include explanations, placeholders, or extra context.
-   - Enclose the command within a code block using `bash` syntax.
 2. **For incomplete or ambiguous instructions:**
-   - **Politely ask** the user for specific missing information.
-   - Do **not** provide any commands or placeholders.
    - Respond in plain text, clearly stating what information is needed.
 3. **For general Kubernetes questions:**
    - Provide a **concise and accurate explanation**.
    - Do **not** include any commands unless specifically requested.
 **Important Rules:**
-- Do **not** generate commands with placeholders or example names like `<pod_name>`.
-- Ensure all commands are **valid and executable** as provided.
-- If unsure due to unclear instructions, **ask for clarification** without including any commands.
-- Do **not** add extra text beyond what's necessary.
----
 ### Instruction:
 {instruction}
 ### Response:
 ```
-### **⚙️ Parameters**
-- **Temperature:** `0.3` (Controls the randomness; lower values make outputs more deterministic.)
-- **Stop Token:** `</s>` (Indicates the end of the assistant's response.)
 ---
-## **🔍 Model Performance**
-### **Enhanced Understanding**
-With **3 billion parameters**, this model provides:
-- **Improved comprehension** of user instructions, even when phrased in complex ways.
-- **Better handling of edge cases** and less common Kubernetes operations.
-### **Consistent Professionalism**
-- Maintains a **professional and courteous tone** in all interactions.
-- **Filters inappropriate language** and focuses on providing assistance.
-### **Examples of Reactions to Questions**
-#### **📗 Generating Complex Commands**
-**User:** "Scale deployment 'backend-service' to 5 replicas."
-**Model Response:**
 ```bash
-kubectl scale deployment backend-service --replicas=5
 ```
-#### **❓ Handling Ambiguity**
-**User:** "Delete the resource."
-**Model Response:**
-"Please specify the type and name of the resource you wish to delete."
-#### **🧠 Explaining Concepts**
-**User:** "Explain how Kubernetes handles Secrets."
-**Model Response:**
-"Kubernetes Secrets allow you to store and manage sensitive information, such as passwords and tokens, in a secure manner. They can be mounted as files or exposed as environment variables in pods."
-#### **🛑 Addressing Inappropriate Language**
-**User:** "What the heck is wrong with this cluster?"
-**Model Response:**
-"Could you please provide more details about the issue you're experiencing with your cluster?"
----
-## **🚀 Deployment with Ollama**
-### **Prerequisites**
-- Install [Ollama](https://github.com/jmorganca/ollama) on your system.
-- Download the GGUF model directly from Hugging Face:
-  ```bash
-  ollama pull hf.co/dereklck/kubectl_operator_3b_peft_gguf
-  ```
-### **Steps to Use the Model**
-1. **Run the Model**
-   ```bash
-   ollama run dereklck/kubectl_operator_3b_peft_gguf
-   ```
-2. **Interact with the Model**
-   Provide your instruction when prompted by the model.
 ---
-## **⚠️ Limitations and Considerations**
-### **Accuracy**
-- While the model aims to generate precise commands, always **review the output** before execution to ensure it's appropriate for your environment.
-### **Handling of Uncommon Scenarios**
-- For highly specialized or unusual Kubernetes commands, the model may not provide the desired output.
-### **Security**
-- Be cautious when executing commands that make changes to your cluster. **Backup important data** and test commands in a safe environment when possible.
 ---
-## **🤝 Feedback and Contributions**
-We welcome feedback and contributions to improve the model and dataset. If you encounter issues or have suggestions:
-- **GitHub:** [Unsloth Repository](https://github.com/unslothai/unsloth)
-- **Contact:** Reach out to **dereklck** for assistance or collaboration opportunities.
----
-## **📄 License**
-This model is released under the **Apache-2.0 License**.
 ---
-## **🏁 Conclusion**
-The **kubectl Operator Model - 3B GGUF** offers a powerful tool for Kubernetes practitioners, providing reliable command generation and valuable explanations. Its enhanced capabilities make it a valuable asset for managing Kubernetes clusters more efficiently.
 ---
-**Note:** This model card provides comprehensive information about the kubectl Operator Model - 3B GGUF, highlighting its features and guiding you on how to deploy and interact with the model effectively.
----
-**Important:** To avoid YAML parsing errors:
-- **Ensure the YAML front matter at the top is properly formatted.**
-- **Avoid including `---` within the content, as it can be misinterpreted as YAML delimiters.**
-- **Use horizontal rules (`***` or `___`) or headings to separate sections instead of `---`.**
 ---
-**Verification:**
-```yaml
-base_model: unsloth/Llama-3.2-3B-Instruct-bnb-4bit
-tags:
-  - text-generation-inference
-  - transformers
-  - unsloth
-  - llama
-  - gguf
-  - ollama
-license: apache-2.0
-language:
-  - en
-```

 ---
+base_model: unsloth/Llama-3.2-3B-Instruct-bnb-4bit
 tags:
+- text-generation-inference
+- transformers
+- unsloth
+- llama
+- gguf
+- ollama
+license: apache-2.0
 language:
+- en
 ---
+# kubectl Operator Model
+- **Developed by:** dereklck
+- **License:** Apache-2.0
+- **Fine-tuned from model:** [unsloth/Llama-3.2-1B-Instruct-bnb-4bit](https://huggingface.co/unsloth/Llama-3.2-1B-Instruct-bnb-4bit)
+- **Model type:** GGUF (compatible with Ollama)
+- **Language:** English
+This Llama-based model was fine-tuned to generate `kubectl` commands based on user descriptions. It 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_3b_peft_gguf`.
+### Steps
+1. **Create the Modelfile**
+   Save the following content as a file named `Modelfile`:
+   ```plaintext
+   FROM hf.co/dereklck/kubernetes_operator_3b_peft_gguf
+   PARAMETER temperature 0.3
+   PARAMETER stop "</s>"
+   TEMPLATE """
+   You are an AI assistant that helps users with Kubernetes commands and questions.
+   **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, or context.
+      - **Enclose the command within a code block** with `bash` syntax highlighting.
+   2. **For incomplete or ambiguous instructions:**
+      - **Politely ask** the user for the specific missing information.
+      - Do **not** provide any commands or placeholders in your response.
+      - Respond in plain text, clearly stating what information is needed.
+   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.
+   **Important Rules:**
+   - **Do not generate CLI commands containing placeholders (e.g., <pod_name>, <resource_name>).**
+   - Ensure all CLI commands are complete, valid, and executable as provided.
+   - If user input is insufficient to form a complete command, ask for clarification instead of using placeholders.
+   - Provide only the necessary CLI command output without any additional text.
+   ### Instruction:
+   {{ .Prompt }}
+   ### Response:
+   {{ .Response }}
+   </s>
+   """
+   ```
+2. **Create the Model with Ollama**
+   Open your terminal and run the following command to create the model:
+   ```bash
+   ollama create kubernetes_operator -f Modelfile
+   ```
+   This command tells Ollama to create a new model named `kubernetes_operator` using the configuration specified in `Modelfile`.
+3. **Run the Model**
+   Start interacting with your model:
+   ```bash
+   ollama run kubernetes_operator
+   ```
+   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_operator -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 descriptions.
+- **Providing brief explanations about Kubernetes** for general queries.
+- **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 Llama-3.2-1B-Instruct-bnb-4bit
+- **Fine-tuning:** Leveraged the Unsloth framework and Hugging Face's TRL library for efficient training.
+- **Training Data:** Customized dataset focused on Kubernetes operations and `kubectl` command usage, containing approximately 200 entries.
+### Features
+- **Command Generation:** Translates user instructions into executable `kubectl` commands.
+- **Clarification Requests:** Politely asks for more details when the instruction is incomplete.
+- **Knowledge Base:** Provides concise explanations for general Kubernetes concepts.
+---
+## Prompt Template
 The model uses the following prompt template to generate responses:
 ```plaintext
 You are an AI assistant that helps users with Kubernetes commands and questions.
+**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, or context.
+   - **Enclose the command within a code block** with `bash` syntax highlighting.
 2. **For incomplete or ambiguous instructions:**
+   - **Politely ask** the user for the specific missing information.
+   - Do **not** provide any commands or placeholders in your response.
    - Respond in plain text, clearly stating what information is needed.
 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.
 **Important Rules:**
+- **Do not generate CLI commands containing placeholders (e.g., <pod_name>, <resource_name>).**
+- Ensure all CLI commands are complete, valid, and executable as provided.
+- If user input is insufficient to form a complete command, ask for clarification instead of using placeholders.
+- Provide only the necessary CLI command output without any additional text.
 ### Instruction:
 {instruction}
 ### Response:
+{response}
 ```
+### Parameters
+- **Temperature:** `0.3` (controls randomness; lower values make outputs more deterministic)
+- **Stop Token:** `</s>` (indicates the end of the assistant's response)
 ---
+## Examples
+### Example 1: Generating a Command
+**Instruction:**
+```
+Create a namespace called 'development'.
+```
+**Response:**
 ```bash
+kubectl create namespace development
 ```
 ---
+### Example 2: Handling Ambiguity
+**Instruction:**
+```
+Show me logs.
+```
+**Response:**
+```
+Which pod's logs would you like to retrieve?
+```
 ---
+### Example 3: Providing Explanations
+**Instruction:**
+```
+What is a Deployment in Kubernetes?
+```
+**Response:**
+```
+A Deployment provides declarative updates for Pods and ReplicaSets, allowing you to manage your applications by defining the desired state and letting Kubernetes handle the rest.
+```
 ---
+## Limitations and Considerations
+- **Accuracy:** The model may occasionally produce incorrect or suboptimal commands. Always review the output before execution.
+- **Hallucinations:** In rare cases, the model might generate irrelevant or incorrect information. If the response seems off-topic, consider rephrasing your instruction.
+- **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 `kubectl` commands based on user input. Always verify the generated commands in a safe environment before executing them in a production cluster.