ACPT docs should be nested inside Ecosystem category in the docs
sidebar, but they currently show up outside of the category at the top
of the sidebar.
Need to add parent to address this issue.
### Description
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### Motivation and Context
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Adding to the docs a link on how to embed an externally compiled engine
and also mention that in case of an embedded engine the builder resource
is not needed.
### Description
Previous footer used an outdated documentation issue template that made
issues more difficult to triage. Updated footer with correct
documentation template.
### Motivation and Context
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### Description
Add an ACPT landing page to the ORT docs to publish supported
configurations + most recent releases
### Motivation and Context
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### Description
Fix broken links referenced in issue #20790
Llama2 blog link was updated to the correct location and ResNet sample
was removed entirely because it no longer exists anywhere in the AML
docs
### Motivation and Context
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Add a section for how to use three major TRT EP caches: TRT timing
cache, TRT engine cache and Embedded engine model /EPContext model.
Some materials are from my GTC slides.
### Description
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update cudnn to 8.9.2.26 (Linux)<br/>8.9.2.26 (Windows)
### Description
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### Description
Fix package name
from ```dotnet add package Microsoft.ML.OnnxRuntimeGenAI.*Cuda*
--prerelease``` to ```dotnet add package
Microsoft.ML.OnnxRuntimeGenAI.DirectML --prerelease``` in DirectML
section.
### Motivation and Context
Clearly confusing for beginners if not fixed (will break further processes)
### Description
Update compatibility/version info for ORT 1.18 release
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### Description
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### Description
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### Motivation and Context
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### Description
Updated blog link so it goes directly to the Hugging Face blog site
### Motivation and Context
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### Description
Add announcement with link to Phi-3 On-Device blog on Hugging Face site
Staged here:
https://sophies927.github.io/onnxruntime/blogs/phi-3-on-device
### Motivation and Context
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### Description
-These changes reflect the latest changes we have made to enable NPU
-Export OpenVINO Blob to ONNX Operator
-Enable QDQ Optimizations Passes
- Separate Device/Precision
### Motivation and Context
These changes reflect the latest changes we have made to enable NPU.
These changes reflect the latest changes we have made to enable rel-1.18
- If it fixes an open issue, please link to the issue here. -->
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Co-authored-by: Preetha Veeramalai <preetha.veeramalai@intel.com>
### Description
This PR updates a reference link in the LLaMA-2 blog post and fixes a
word formatting issue.
### Motivation and Context
With these changes, the link to the example E2E notebook works again.
### Description
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* Update TRT version to 10.0
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### Description
Addresses #20096, and checked #20261 (should have already been fixed)
Also added a different animation for words on the hero as they didn't
look good (some svelte animation bug I think)
Link found at: https://maanavd.github.io/onnxruntime/
Co-authored-by: MaanavD <maanavdalal@microsoft.com>
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Co-authored-by: MaanavD <maanavdalal@microsoft.com>
### Description
with-python.md does not currently include installation instructions for
CUDA 12.X, so I added the instructions from
https://onnxruntime.ai/docs/execution-providers/CUDA-ExecutionProvider.html#requirements.
### Motivation and Context
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### Description
File previously included TOC placeholder instead of actual TOC
### Motivation and Context
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### Description
CUDA-ExecutionProvider.md table of contents previously not showing up
correctly b/c of spacing issue.
### Motivation and Context
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Update the document for PR: Enable Cross-Compiling Support for ONNX
Runtime on Linux for RISC-V 64-bit.
https://github.com/microsoft/onnxruntime/pull/19238
Signed-off-by: Phoebe Chen <phoebe.chen@sifive.com>
- doc suggests that QDQ model are created with dynamic quant, which is
not the case anymore.
- updating and restructuring the doc
### Description
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- QDQ model format representation doesn't come for dynamic quantization,
but the doc was suggesting.
- May be a couple of years back this support was there but not anymore
### Motivation and Context
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- Clears misunderstanding that QDQ Onnx models can be created with
dynamic quantization.
https://github.com/microsoft/onnxruntime/issues/20125
Get Started table currently only includes instructions for
Windows/Python/X64/CUDA and Linux/Python/X64/CUDA for (default) CUDA
11.8. Updating to include installation instructions for CUDA 12.X as
well.
