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docs: add models directory (#437)
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---
sidebar_position: 4
---
# 🧑‍🔬 Models Directory
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We recommend using
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* **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**.
| Model ID | License |
| ---------------------------------------------------------------------- | ------------------------------------------------------------------------------------------- |
| [TabbyML/CodeLlama-13B](https://huggingface.co/TabbyML/CodeLlama-13B) | [Llama2](https://github.com/facebookresearch/llama/blob/main/LICENSE) |
| [TabbyML/CodeLlama-7B](https://huggingface.co/TabbyML/CodeLlama-7B) | [Llama2](https://github.com/facebookresearch/llama/blob/main/LICENSE) |
| [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) |
| [TabbyML/SantaCoder-1B](https://huggingface.co/TabbyML/SantaCoder-1B) | [BigCode-OpenRAIL-M](https://huggingface.co/spaces/bigcode/bigcode-model-license-agreement) |
| [TabbyML/WizardCoder-3B](https://huggingface.co/TabbyML/WizardCoder-3B)| [OpenRAIL-M](https://huggingface.co/spaces/bigcode/bigcode-model-license-agreement) |
| [TabbyML/WizardCoder-1B](https://huggingface.co/TabbyML/WizardCoder-1B)| [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 <span title="Apple GPU Support"></span>
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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 <span title="Apple GPU Support"></span>
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docs: add starcoder 3b/7b (#451) * docs: add starcoder 3b/7b * Update index.md
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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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docs: add wizardcoder models (#467) * Update README.md test * Update on 10k stars. * Update README.md on 10k stars. * doc: add wizardcoder models
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### WizardCoder-1B / WizardCoder-3B <span title="Apple GPU Support"></span>
WizardCoder [(arXiv)](https://arxiv.org/abs/2306.08568) series model are finetuned on StarCoder models with the Evol-Instruct method to adapt to coding tasks. Note that WizardCoder models have used GPT-4 generated data for finetuning, and thus adhere to [OpenAI's limitations](https://openai.com/policies/terms-of-use) for model usage.
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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.