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`stable-code-instruct-3b` is a 2.7B billion parameter decoder-only language model tuned from [`stable-code-3b`](https://huggingface.co/stabilityai/stable-code-3b/). This model was trained on a mix of publicly available datasets, synthetic datasets using [Direct Preference Optimization (DPO)](https://arxiv.org/abs/2305.18290).
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This instruct tune demonstrates state-of-the-art performance (compared to models of similar size) on the MultiPL-E metrics across multiple programming languages tested using [BigCode's Evaluation Harness](https://github.com/bigcode-project/bigcode-evaluation-harness/tree/main), and on the code portions of
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[MT Bench](https://klu.ai/glossary/mt-bench-eval)
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## Usage
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| DeepSeek Coder | 1.3B | 4.6 |
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| Stable Code Instruct (DPO) | 3B | **5.8**(ours) |
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| Stable Code Instruct (SFT) | 3B | 5.5 |
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| CodeLlama Instruct | 7B | 3.55 |
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| DeepSeek Coder | 6.7B | **6.9** |
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| StarChat2 | 15B | 5.7 |
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`stable-code-instruct-3b` is a 2.7B billion parameter decoder-only language model tuned from [`stable-code-3b`](https://huggingface.co/stabilityai/stable-code-3b/). This model was trained on a mix of publicly available datasets, synthetic datasets using [Direct Preference Optimization (DPO)](https://arxiv.org/abs/2305.18290).
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This instruct tune demonstrates state-of-the-art performance (compared to models of similar size) on the MultiPL-E metrics across multiple programming languages tested using [BigCode's Evaluation Harness](https://github.com/bigcode-project/bigcode-evaluation-harness/tree/main), and on the code portions of
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[MT Bench](https://klu.ai/glossary/mt-bench-eval).
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The model is finetuned to make it useable in tasks like,
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- General purpose Code/Software Engineering like conversations.
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- Function Calling
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- SQL related generation and conversation.
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## Usage
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| DeepSeek Coder | 1.3B | 4.6 |
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| Stable Code Instruct (DPO) | 3B | **5.8**(ours) |
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| Stable Code Instruct (SFT) | 3B | 5.5 |
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| DeepSeek Coder | 6.7B | **6.9** |
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| CodeLlama Instruct | 7B | 3.55 |
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| StarChat2 | 15B | 5.7 |
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