This is quantized version of JetBrains/CodeLlama-7B-KStack created using llama.cpp This is a repository for the CodeLlama-7b model fine-tuned on the KStack dataset with rule-based filtering, in the Hugging Face Transformers format. KStack is the largest collection of permissively licensed Kotlin code, and so the model is fine-tuned to work better with Kotlin code. As with the base model, we can use FIM. To do this, the following format must be used: The model was trained on one A100 GPU with following hyperparameters: More details about fine-tuning can be found in the technical report (coming soon!). For tuning the model, we used the KStack dataset, the largest collection of permissively licensed Kotlin code. To increase the quality of the dataset and filter out outliers, such as homework assignments, we filter out the dataset entries according to the following rules: We filter out files, which belong to low-popular repos (the sum of stars and forks is less than 6) Next, we filter out files, which belong to repos with less than 5 Kotlin files * Finally, we remove files which have fewer than 20 SLOC We clean the content of the remaining dataset entries according to the following…
Модальности:
Генерация текста
Области применения:
Генерация кода
Задача: Генерация текста
Автор: QuantFactory
Теги: gguf, code, endpoints_compatible
Лайков: 3 | Загрузок: 699
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
