---
license: mit
datasets:
- adeeshajayasinghe/devops-guide-demo
metrics:
- accuracy
base_model:
- microsoft/phi-2
new_version: microsoft/phi-2
pipeline_tag: text-generation
library_name: transformers
tags:
- code
- text-generation-inference
---

# DevOps Mastermind Model

This repository hosts the **DevOps Mastermind** model, a pre-trained model based on `microsoft/phi-2` with modifications tailored for specialized DevOps knowledge tasks. The model is designed to support various downstream tasks, such as code generation, documentation assistance, and knowledge inference in DevOps domains.

## Model Details

- **Base Model**: `microsoft/phi-2`
- **Purpose**: Enhanced with additional training and modifications for DevOps and software engineering contexts.
- **Files Included**:
  - `config.json`: Model configuration.
  - `pytorch_model.bin`: The primary model file containing weights.
  - `tokenizer.json`: Tokenizer for processing text inputs.
  - `added_tokens.json`: Additional tokens specific to DevOps vocabulary.
  - `generation_config.json`: Generation configuration for text generation tasks.
  - Other auxiliary files required for model usage and compatibility.

## Usage

To load and use this model in your code, run the following commands:

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

# Load the model and tokenizer
model_name = "kavinduc/devops-mastermind"
model = AutoModelForCausalLM.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=False)

# Example usage
input_text = "Explain how to set up a CI/CD pipeline"
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs)
generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(generated_text)