--- license: apache-2.0 datasets: - JetBrains/KStack results: - task: type: text-generation dataset: name: MultiPL-HumanEval (Kotlin) type: openai_humaneval metrics: - name: pass@1 type: pass@1 value: 29.19 tags: - code quantized_by: bartowski pipeline_tag: text-generation lm_studio: param_count: 7b use_case: code completion release_date: 21-05-2024 model_creator: JetBrains prompt_template: none system_prompt: none base_model: CodeLlama-7b original_repo: JetBrains/CodeLlama-7B-KStack base_model: JetBrains/CodeLlama-7B-KStack --- ## 💫 Community Model> CodeLlama 7B KStack by JetBrains *👾 [LM Studio](https://lmstudio.ai) Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on [Discord](https://discord.gg/aPQfnNkxGC)*. **Model creator:** [JetBrains](https://huggingface.co/JetBrains)
**Original model**: [CodeLlama-7B-KStack](https://huggingface.co/JetBrains/CodeLlama-7B-KStack)
**GGUF quantization:** provided by [bartowski](https://huggingface.co/bartowski) based on `llama.cpp` release [b2965](https://github.com/ggerganov/llama.cpp/releases/tag/b2965)
## Model Summary: This model is designed to be used exclusive for code completion and tuned specifically for Kotlin.
Use this model as a coding assistant and for completion in your IDE to generate strong Kotlin code. ## Prompt template: There is no prompt template for this model, it should be used for completion. ## Technical Details This model is based on the CodeLlama-7b and trained on the KStack dataset found here: https://huggingface.co/datasets/JetBrains/KStack
The dataset was filtered and cleaned for quality prior to training.
It supports FIM tokens: - `'
 ' + prefix + '  ' + suffix + ' '`

## Special thanks

🙏 Special thanks to [Georgi Gerganov](https://github.com/ggerganov) and the whole team working on [llama.cpp](https://github.com/ggerganov/llama.cpp/) for making all of this possible.

🙏 Special thanks to [Kalomaze](https://github.com/kalomaze), [Dampf](https://github.com/Dampfinchen) and [turboderp](https://github.com/turboderp/) for their work on the dataset (linked [here](https://gist.github.com/bartowski1182/b6ac44691e994344625687afe3263b3a)) that was used for calculating the imatrix for all sizes.

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