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Models Directory

StableCode Instruct State-of-the-art for low Spec machines(Released 8th August 2023)

StableCode Instruct is a new model from Stability.ai which provides reasonable autocomplete suggestions in approx 3GiB of RAM.

Model Name RAM Requirement Direct Download HF Project Link
StableCode ~3GiB ⬇️ 🤗

To run in Turbopilot set model type -m stablecode

"Coder" family models

WizardCoder, StarCoder and SantaCoder are current "state-of-the-art" autocomplete models

SantaCoder (Small Model, Reasonable on lower spec machines - Released 13/4/2023)

SantaCoder is a smaller version of the StarCoder and WizardCoder family with only 1.1 Billion parameters. The model is trained with fill-in-the-middle objective allowing it to be used to auto-complete function parameters.

This model is primarily trained on Python, Java and Javscript.

Model Name RAM Requirement Direct Download HF Project Link
SantaCoder ~2GiB ⬇️ 🤗

To run in Turbopilot set model type -m starcoder

WizardCoder 15B Best Autocomplete Performance, Compute-Hungry (Released 15/6/2023)

WizardCoder is the current SOTA auto complete model, it is an updated version of StarCoder that achieves 57.1 pass@1 on HumanEval benchmarks (essentially in 57% of cases it correctly solves a given challenge. Read more about how this metric works in the scientific paper here ).

Even when quantized, WizardCoder is a large model that takes up a significant amount of RAM.

Model Name RAM Requirement Direct Download HF Project Link
WizardCoder ~12GiB ⬇️ 🤗

To run in Turbopilot set model type -m wizardcoder

StarCoder (Released 4/5/2023)

StarCoder held the previous title of state-of-the-art coding model back in May 2023. It is still a reasonably good model by comparison but it is a similar size and has similar RAM and compute requirements to WizardCoder so you may be better off just running that. Links below provided for posterity.

Model Name RAM Requirement Direct Download HF Project Link
StarCoder ~12GiB ⬇️ 🤗
StarCoder Plus ~12GiB ⬇️ 🤗

To run in Turbopilot set model type -m starcoder

CodeGen 1.0

The CodeGen models were the first models supported by Turbopilot. They perform less well than the newer Wizardcoder/Starcoder/Santacoder variant models.

The multi flavour models can provide auto-complete suggestions for C, C++, Go, Java, JavaScript, and Python.

The mono flavour models can provide auto-complete suggestions for Python only (but the quality of Python-specific suggestions may be higher).

Pre-converted and pre-quantized models are available for download from here:

Model Name RAM Requirement Supported Languages Direct Download HF Project Link
CodeGen 350M multi ~800MiB C, C++, Go, Java, JavaScript, Python ⬇️ 🤗
CodeGen 350M mono ~800MiB Python ⬇️ 🤗
CodeGen 2B multi ~4GiB C, C++, Go, Java, JavaScript, Python ⬇️ 🤗
CodeGen 2B mono ~4GiB Python ⬇️ 🤗
CodeGen 6B multi ~8GiB C, C++, Go, Java, JavaScript, Python ⬇️ 🤗
CodeGen 6B mono ~8GiB Python ⬇️ 🤗