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README.md
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@@ -27,7 +27,7 @@ Este documento ofrece una visión detallada de `GemmaColRAC-AeroExpertV5`, la qu
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## Metadatos del Nuevo Modelo
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- **Nombre del Modelo:** GemmaColRAC-AeroExpertV4
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- **Tipo de GPU:** NVIDIA GeForce RTX 3090
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- **Tiempo Total de Entrenamiento:** 12607 segundos
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Given the use of an NVIDIA V100 GPU for approximately 4.67 hours, the carbon emissions can be estimated using the Machine Learning Impact calculator. This tool accounts for the hardware type, runtime, and other factors to provide a comprehensive view of the environmental impact of training large AI models.
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- **Hardware Type:** NVIDIA
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- **Hours used:** ~3.0
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- **Carbon Emitted:** 356.25
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## Metadatos del Nuevo Modelo
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- **Developed by:** [Edison Bejarano](https://huggingface.co/ejbejaranos), [Nicolai Potes](https://huggingface.co/NickyNicky) and [Santiago Pineda](https://huggingface.co/Sapinedamo) ✨
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- **Nombre del Modelo:** GemmaColRAC-AeroExpertV4
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- **Tipo de GPU:** NVIDIA GeForce RTX 3090
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- **Tiempo Total de Entrenamiento:** 12607 segundos
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Given the use of an NVIDIA V100 GPU for approximately 4.67 hours, the carbon emissions can be estimated using the Machine Learning Impact calculator. This tool accounts for the hardware type, runtime, and other factors to provide a comprehensive view of the environmental impact of training large AI models.
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- **Hardware Type:** NVIDIA 3090 GPU
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- **Hours used:** ~3.0
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- **Carbon Emitted:** 356.25
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