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belka13/phi-1_5-finetuned-kotlin
phi-1_5-finetuned-kotlin is a machine learning model from belka13. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
This is a 🤗 transformers model card that was pre-trained on a dataset built from the JetBrains Kotlin repository on GitHub and uploaded to Hub. This model card was generated automatically.
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Updated May 5, 2024
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From the Hugging Face model README
This is a 🤗 transformers model card that was pre-trained on a dataset built from the JetBrains Kotlin repository on GitHub and uploaded to Hub. This model card was generated automatically.
The model is a language model pre-trained on Kotlin code from the JetBrains Kotlin repository on GitHub. It is designed to complete and understand code in these programming languages.
The model can be used to augment Kotlin and Python code, finding bugs and style inconsistencies in existing code. It can also help in understanding and documenting code bases.
The model is not intended to generate arbitrary text or code in programming languages other than Kotlin and Python. It should also not be used to automatically make changes to production code without human review.
The model may have biases and limitations based on code in the JetBrains Kotlin repository. The generated code may not conform to best practices or may contain bugs and vulnerabilities.
Users should be aware of the risks, biases and limitations of the model. Model-generated code should always be tested by experienced developers before use in production. The model is best suited for auxiliary purposes, such as learning Kotlin/Python syntax and style, rather than for writing production code yourself.
The following metrics were used to evaluate the model in Kotlin and Python:
| Model | Dataset | Accuracy | Perplexity |
|---|---|---|---|
| Default | Kotlin | 0.0031 | 94.78 |
| Python | 0.0067 | 6.67 | |
| Fine-tuned | Kotlin | 0.0096 | 62.82 |
| Python | 0.0180 | 5.71 |