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--- |
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license: mit |
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datasets: |
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- adeeshajayasinghe/devops-guide-demo |
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metrics: |
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- accuracy |
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base_model: |
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- microsoft/phi-2 |
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new_version: microsoft/phi-2 |
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pipeline_tag: text-generation |
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library_name: transformers |
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tags: |
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- code |
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- text-generation-inference |
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--- |
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# DevOps Mastermind Model |
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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. |
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## Model Details |
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- **Base Model**: `microsoft/phi-2` |
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- **Purpose**: Enhanced with additional training and modifications for DevOps and software engineering contexts. |
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- **Files Included**: |
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- `config.json`: Model configuration. |
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- `pytorch_model.bin`: The primary model file containing weights. |
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- `tokenizer.json`: Tokenizer for processing text inputs. |
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- `added_tokens.json`: Additional tokens specific to DevOps vocabulary. |
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- `generation_config.json`: Generation configuration for text generation tasks. |
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- Other auxiliary files required for model usage and compatibility. |
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## Usage |
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To load and use this model in your code, run the following commands: |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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# Load the model and tokenizer |
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model_name = "kavinduc/devops-mastermind" |
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model = AutoModelForCausalLM.from_pretrained(model_name) |
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tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=False) |
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# Example usage |
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input_text = "Explain how to set up a CI/CD pipeline" |
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inputs = tokenizer(input_text, return_tensors="pt") |
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outputs = model.generate(**inputs) |
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generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True) |
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print(generated_text) |
