---
library_name: transformers
license: llama3.1
language:
- ru
- en
base_model:
- meta-llama/Llama-3.1-8B-Instruct
pipeline_tag: text-generation
---

# Model Card

Devple is a fine-tuned model based on Llama 3.1 Instruct, designed for development tasks such as code generation and review, with a focus on the quality and safety of the generated code. Its synthetic dataset was generated using GPT-4o with Llama-3 (rejected).



## Model Details

### Model Description

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Devple is a fine-tuned model based on Llama 3.1 Instruct. The model is built on a synthetic dataset. The main focus of the training was on development-related tasks such as code generation, code review, refactoring, etc., with particular emphasis on the quality and safety of the generated code.

Fine-tuning was done using ORPO. The dataset was generated using GPT-4o (selected) and Llama-3 (rejected).

- **Language(s) (NLP):** English, Russian
- **Finetuned from model:** Llama 3.1 Instruct

### Model Sources [optional]

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## Uses

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### Direct Use

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### Downstream Use [optional]

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### Out-of-Scope Use

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## Bias, Risks, and Limitations

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### Recommendations

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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

## How to Get Started with the Model

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## Training Details

### Training Data

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### Training Procedure

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#### Preprocessing [optional]

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#### Training Hyperparameters

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#### Speeds, Sizes, Times [optional]

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## Evaluation

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### Testing Data, Factors & Metrics

#### Testing Data

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#### Factors

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#### Metrics

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### Results

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#### Summary



## Model Examination [optional]

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## Environmental Impact

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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

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## Technical Specifications [optional]

### Model Architecture and Objective

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### Compute Infrastructure

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#### Hardware

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#### Software

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## Citation [optional]

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**APA:**

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## Glossary [optional]

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## Model Card Authors [optional]

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## Model Card Contact

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