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@@ -85,7 +85,7 @@ StarCoder2-15B model is a 15B parameter model trained on 600+ programming langua
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  The model was trained with [NVIDIA NeMo™ Framework](https://www.nvidia.com/en-us/ai-data-science/generative-ai/nemo-framework/) using the [NVIDIA Eos Supercomputer](https://blogs.nvidia.com/blog/eos/) built with [NVIDIA DGX H100](https://www.nvidia.com/en-us/data-center/dgx-h100/) systems.
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  - **Project Website:** [bigcode-project.org](https://www.bigcode-project.org)
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- - **Paper:** [Link](https://drive.google.com/file/d/17iGn3c-sYNiLyRSY-A85QOzgzGnGiVI3/view?usp=sharing)
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  - **Point of Contact:** [contact@bigcode-project.org](mailto:contact@bigcode-project.org)
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  - **Languages:** 600+ Programming languages
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@@ -174,7 +174,7 @@ The pretraining dataset of the model was filtered for permissive licenses and co
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  # Limitations
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- The model has been trained on source code from 600+ programming languages. The predominant language in source is English although other languages are also present. As such the model is capable to generate code snippets provided some context but the generated code is not guaranteed to work as intended. It can be inefficient, contain bugs or exploits. See [the paper](https://drive.google.com/file/d/17iGn3c-sYNiLyRSY-A85QOzgzGnGiVI3/view?usp=sharing) for an in-depth discussion of the model limitations.
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  # Training
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  The model was trained with [NVIDIA NeMo™ Framework](https://www.nvidia.com/en-us/ai-data-science/generative-ai/nemo-framework/) using the [NVIDIA Eos Supercomputer](https://blogs.nvidia.com/blog/eos/) built with [NVIDIA DGX H100](https://www.nvidia.com/en-us/data-center/dgx-h100/) systems.
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  - **Project Website:** [bigcode-project.org](https://www.bigcode-project.org)
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+ - **Paper:** [Link](https://huggingface.co/papers/2402.19173)
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  - **Point of Contact:** [contact@bigcode-project.org](mailto:contact@bigcode-project.org)
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  - **Languages:** 600+ Programming languages
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  # Limitations
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+ The model has been trained on source code from 600+ programming languages. The predominant language in source is English although other languages are also present. As such the model is capable to generate code snippets provided some context but the generated code is not guaranteed to work as intended. It can be inefficient, contain bugs or exploits. See [the paper](https://huggingface.co/papers/2402.19173) for an in-depth discussion of the model limitations.
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  # Training
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