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@@ -18,7 +18,7 @@ they simplify geospatial model training and deployment, making it accessible
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  for open science users, startups, and enterprises on multi-cloud AI platforms
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  like [watsonx](https://www.ibm.com/watsonx). Additionally, Hugging Face enables easy sharing of the pipelines of the model family, which
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  our team calls [Prithvi](https://huggingface.co/ibm-nasa-geospatial/Prithvi-100M), within the community, fostering global collaboration and engagement. More details on Prithvi can be found
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- in the joint IBM NASA [technical paper](https://arxiv.org/abs/2310.18660).
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  <a rel="noopener nofollow" class="block overflow-hidden" href="https://youtu.be/9bU9eJxFwWc">
 
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  for open science users, startups, and enterprises on multi-cloud AI platforms
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  like [watsonx](https://www.ibm.com/watsonx). Additionally, Hugging Face enables easy sharing of the pipelines of the model family, which
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  our team calls [Prithvi](https://huggingface.co/ibm-nasa-geospatial/Prithvi-100M), within the community, fostering global collaboration and engagement. More details on Prithvi can be found
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+ in the joint IBM NASA [technical paper](https://arxiv.org/abs/2310.18660). For more enterprise-ready finetuned versions of the Prithvi model, please visit the [IBM Granite Hugging Face page](https://huggingface.co/collections/ibm-granite/granite-geospatial-models-667dacfed21bdcf60a8bc982).
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  <a rel="noopener nofollow" class="block overflow-hidden" href="https://youtu.be/9bU9eJxFwWc">