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@@ -25,28 +25,5 @@ In this profile we provide accurate model checkpoints compressed with SOTA metho
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If you would like help quantizing a model or have a request for us to add a checkpoint, please open an issue in https://github.com/vllm-project/llm-compressor.
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### Additional Red Hat AI Resources:
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RHEL AI/Instructlab/Granite Blog
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https://www.redhat.com/en/blog/what-rhel-ai-guide-open-source-way-doing-ai
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InstructLab
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https://github.com/instructlab
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RHEL AI Preview
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https://github.com/RedHatOfficial/rhelai-dev-preview
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Red Hat OpenShift AI (ML/Ops Platform)
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https://www.redhat.com/en/technologies/cloud-computing/openshift/openshift-ai
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IBM Watsonx and OpenSource (integrated with OpenShift AI)
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https://developer.ibm.com/articles/awb-the-open-source-ecosystem-of-watsonx/
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Podman AI Lab for local desktop experimentation
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https://github.com/containers/podman-desktop-extension-ai-lab
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Red Hat Research paper: "Building Trust: Foundations of Security, Safety and Transparency in AI"
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https://arxiv.org/abs/2411.12275
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If you would like help quantizing a model or have a request for us to add a checkpoint, please open an issue in https://github.com/vllm-project/llm-compressor.
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Learn more at https://www.redhat.com/en/products/ai
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