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# 🧑🔬 Models Directory
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We recommend using
* small models (less than 400M) for CPU devices.
* For 1B to 7B models, it's advisable to have at least NVIDIA T4, 10 Series, or 20 Series GPUs.
* For 7B to 13B models, we recommend using NVIDIA V100, A100, 30 Series, or 40 Series GPUs.
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| Model ID | License | < span title = "Apple M1/M2 Only" > Metal Support< / span > |
| --------------------------------------------------------------------- | ------------------------------------------------------------------------------------------- | :-------------------------------------------------: |
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| [TabbyML/CodeLlama-13B ](https://huggingface.co/TabbyML/CodeLlama-13B ) | [Llama2 ](https://github.com/facebookresearch/llama/blob/main/LICENSE ) | ✅ |
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| [TabbyML/CodeLlama-7B ](https://huggingface.co/TabbyML/CodeLlama-7B ) | [Llama2 ](https://github.com/facebookresearch/llama/blob/main/LICENSE ) | ✅ |
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| [TabbyML/StarCoder-7B ](https://huggingface.co/TabbyML/StarCoder-7B ) | [BigCode-OpenRAIL-M ](https://huggingface.co/spaces/bigcode/bigcode-model-license-agreement ) | 🔜 |
| [TabbyML/StarCoder-3B ](https://huggingface.co/TabbyML/StarCoder-3B ) | [BigCode-OpenRAIL-M ](https://huggingface.co/spaces/bigcode/bigcode-model-license-agreement ) | 🔜 |
| [TabbyML/StarCoder-1B ](https://huggingface.co/TabbyML/StarCoder-1B ) | [BigCode-OpenRAIL-M ](https://huggingface.co/spaces/bigcode/bigcode-model-license-agreement ) | 🔜 |
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| [TabbyML/SantaCoder-1B ](https://huggingface.co/TabbyML/SantaCoder-1B ) | [BigCode-OpenRAIL-M ](https://huggingface.co/spaces/bigcode/bigcode-model-license-agreement ) | ❌ |
| [TabbyML/J-350M ](https://huggingface.co/TabbyML/J-350M ) | [BSD-3 ](https://opensource.org/license/bsd-3-clause/ ) | ❌ |
| [TabbyML/T5P-220M ](https://huggingface.co/TabbyML/T5P-220M ) | [BSD-3 ](https://opensource.org/license/bsd-3-clause/ ) | ❌ |
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### CodeLlama-7B / CodeLlama-13B
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Code Llama is a collection of pretrained and fine-tuned generative text models. Theses model is designed for general code synthesis and understanding.
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### StarCoder-1B / StarCoder-3B / StarCoder-7B
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StarCoder series model are trained on 80+ programming languages from The Stack (v1.2), with opt-out requests excluded. The model uses Multi Query Attention, a context window of 8192 tokens, and was trained using the Fill-in-the-Middle objective on 1 trillion tokens.
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### SantaCoder-1B
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SantaCoder is the smallest member of the BigCode family of models, boasting just 1.1 billion parameters. This model is specifically trained with a fill-in-the-middle objective, enabling it to efficiently auto-complete function parameters. It offers support for three programming languages: Python, Java, and JavaScript.
### J-350M
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Derived from [Salesforce/codegen-350M-multi ](https://huggingface.co/Salesforce/codegen-350M-multi ), a model of CodeGen family.
### T5P-220M
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Derived from [Salesforce/codet5p-220m ](https://huggingface.co/Salesforce/codet5p-220m ), a model of CodeT5+ family.
