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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,241 @@
+---
+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
+
+---
+
+# Hybrid Kubernetes Feature Model
+
+- **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 (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 descriptions.
+2. **Providing concise explanations about Kubernetes** for general queries.
+3. **Politely requesting additional information** if the instruction is incomplete or ambiguous.
+
+**Update:** Compared to the previous 1B model, the **3B model significantly reduces hallucinations** that sometimes occurred in the 1B model. Users can expect improved accuracy and reliability 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_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 hybrid_kubernetes_feature_model -f Modelfile
+   ```
+
+   This command tells Ollama to create a new model named `hybrid_kubernetes_feature_model` using the configuration specified in `Modelfile`.
+
+3. **Run the Model**
+
+   Start interacting with your model:
+
+   ```bash
+   ollama run hybrid_kubernetes_feature_model
+   ```
+
+   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 hybrid_kubernetes_feature_model -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 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 Llama-3.2-3B-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 features, including `kubectl` command usage and general Kubernetes concepts, containing 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 3B Model
+
+The transition to the 3B model has significantly **reduced hallucinations** that sometimes occurred in the 1B model. The 3B model provides more accurate and reliable responses, improving the overall user experience.
+
+---
+
+## 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:** While the 3B model improves accuracy, the model may occasionally produce incorrect or suboptimal commands. Always review the output before execution.
+- **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.
+
+---
+
+If you have any further requests or need additional adjustments, please let me know!

adapter_config.json

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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128251": {
+      "content": "<|reserved_special_token_243|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128252": {
+      "content": "<|reserved_special_token_244|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128253": {
+      "content": "<|reserved_special_token_245|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128254": {
+      "content": "<|reserved_special_token_246|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128255": {
+      "content": "<|reserved_special_token_247|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<|begin_of_text|>",
+  "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n    {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n    {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not date_string is defined %}\n    {%- if strftime_now is defined %}\n        {%- set date_string = strftime_now(\"%d %b %Y\") %}\n    {%- else %}\n        {%- set date_string = \"26 Jul 2024\" %}\n    {%- endif %}\n{%- endif %}\n{%- if not tools is defined %}\n    {%- set tools = none %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[0]['role'] == 'system' %}\n    {%- set system_message = messages[0]['content']|trim %}\n    {%- set messages = messages[1:] %}\n{%- else %}\n    {%- set system_message = \"\" %}\n{%- endif %}\n\n{#- System message #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if tools is not none %}\n    {{- \"Environment: ipython\\n\" }}\n{%- endif %}\n{{- \"Cutting Knowledge Date: December 2023\\n\" }}\n{{- \"Today Date: \" + date_string + \"\\n\\n\" }}\n{%- if tools is not none and not tools_in_user_message %}\n    {{- \"You have access to the following functions. To call a function, please respond with JSON for a function call.\" }}\n    {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n    {{- \"Do not use variables.\\n\\n\" }}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\\n\\n\" }}\n    {%- endfor %}\n{%- endif %}\n{{- system_message }}\n{{- \"<|eot_id|>\" }}\n\n{#- Custom tools are passed in a user message with some extra guidance #}\n{%- if tools_in_user_message and not tools is none %}\n    {#- Extract the first user message so we can plug it in here #}\n    {%- if messages | length != 0 %}\n        {%- set first_user_message = messages[0]['content']|trim %}\n        {%- set messages = messages[1:] %}\n    {%- else %}\n        {{- raise_exception(\"Cannot put tools in the first user message when there's no first user message!\") }}\n{%- endif %}\n    {{- '<|start_header_id|>user<|end_header_id|>\\n\\n' -}}\n    {{- \"Given the following functions, please respond with a JSON for a function call \" }}\n    {{- \"with its proper arguments that best answers the given prompt.\\n\\n\" }}\n    {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n    {{- \"Do not use variables.\\n\\n\" }}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\\n\\n\" }}\n    {%- endfor %}\n    {{- first_user_message + \"<|eot_id|>\"}}\n{%- endif %}\n\n{%- for message in messages %}\n    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n    {%- elif 'tool_calls' in message %}\n        {%- if not message.tool_calls|length == 1 %}\n            {{- raise_exception(\"This model only supports single tool-calls at once!\") }}\n        {%- endif %}\n        {%- set tool_call = message.tool_calls[0].function %}\n        {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n        {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n        {{- '\"parameters\": ' }}\n        {{- tool_call.arguments | tojson }}\n        {{- \"}\" }}\n        {{- \"<|eot_id|>\" }}\n    {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n        {{- \"<|start_header_id|>ipython<|end_header_id|>\\n\\n\" }}\n        {%- if message.content is mapping or message.content is iterable %}\n            {{- message.content | tojson }}\n        {%- else %}\n            {{- message.content }}\n        {%- endif %}\n        {{- \"<|eot_id|>\" }}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}\n",
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|eot_id|>",
+  "extra_special_tokens": {},
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 131072,
+  "pad_token": "<|finetune_right_pad_id|>",
+  "padding_side": "left",
+  "tokenizer_class": "PreTrainedTokenizerFast",
+  "unk_token": null
+}