diff --git a/src/images/events/converttoort.jpg b/src/images/events/converttoort.jpg
new file mode 100644
index 0000000000..8c3f16fb97
Binary files /dev/null and b/src/images/events/converttoort.jpg differ
diff --git a/src/images/undraw/image_events.svelte b/src/images/undraw/image_events.svelte
new file mode 100644
index 0000000000..ff58f54ea9
--- /dev/null
+++ b/src/images/undraw/image_events.svelte
@@ -0,0 +1,216 @@
+
diff --git a/src/routes/+page.svelte b/src/routes/+page.svelte
index 06be1531da..b84f7fc769 100644
--- a/src/routes/+page.svelte
+++ b/src/routes/+page.svelte
@@ -2,7 +2,7 @@
import Hero from './components/hero.svelte';
import Customers from './components/customers.svelte';
import CodeBlocks from './components/code-blocks.svelte';
- import Videos from './components/videos.svelte';
+ import VideoGallery from './components/videogallery.svelte';
import Performance from './components/performance.svelte';
import CrossPlatform from './components/cross-platform.svelte';
import GenerativeAi from './components/generative-ai-hero.svelte';
@@ -16,6 +16,21 @@
e.target.parentNode.parentNode.remove();
};
+ let videos = [
+ {
+ title: 'What is ONNX Runtime (ORT)?',
+ link: 'https://www.youtube.com/embed/M4o4YRVba4o?si=LHc-2AhKt3TrY60g'
+ },
+ {
+ title: 'Converting Models to ONNX Format',
+ link: 'https://www.youtube.com/embed/lRBsmnBE9ZA?si=l5i0Q2P7VtSJyGK1'
+ },
+ {
+ title: 'Optimize Training and Inference with ONNX Runtime (ORT/ACPT/DeepSpeed)',
+ link: 'https://www.youtube.com/embed/lC7d_7waHLM?si=U4252VEd1t5ioZUN'
+ }
+ ];
+
onMount(() => {
anime({
targets: '.toast',
@@ -33,7 +48,7 @@
-
+
diff --git a/src/routes/blogs/+page.svelte b/src/routes/blogs/+page.svelte
index 9435678962..8e8dfcecf9 100644
--- a/src/routes/blogs/+page.svelte
+++ b/src/routes/blogs/+page.svelte
@@ -9,11 +9,12 @@
import HFImage from '../../images/blogs/hugging-face-blog-img.png';
import LlamaImage from '../../images/blogs/accelerating-llama-2/Figure1-LLaMA-2-7B-E2E-Throughput.png';
import SDXLTurboImage from '../../images/blogs/sdxl_blog_thumbnail.png';
+ import { createEventDispatcher } from 'svelte';
import WebTrainingImage from '../../images/blogs/webtraining_blog_thumbnail.png';
onMount(() => {
anime({
targets: '.border-primary',
- translateY: -20,
+ translateY: -5,
direction: 'alternate',
loop: false,
delay: function (el, i, l) {
@@ -24,6 +25,18 @@
}
});
});
+
+ let showBlogs = true;
+ const dispatch = createEventDispatcher();
+
+ onMount(() => {
+ dispatch('switchTab', 'blogs');
+ });
+
+ function switchTab(tab) {
+ showBlogs = tab === 'blogs';
+ dispatch('switchTab', tab);
+ }
let featuredblog = [
{
title: 'On-Device Training: Training a model in browser',
@@ -61,7 +74,7 @@
link: 'blogs/pytorch-on-the-edge',
image:
'https://onnxruntime.ai/_app/immutable/assets/pytorch-on-the-edge-with-ort.cdaa9c84.png',
- imgalt: 'Run PyTorch models on the edge'
+ imgalt: 'Run PyTorch models on the edge'
},
{
title: 'Accelerating over 130,000 Hugging Face models with ONNX Runtime',
@@ -258,6 +271,28 @@
link: 'https://cloudblogs.microsoft.com/opensource/2021/06/30/journey-to-optimize-large-scale-transformer-model-inference-with-onnx-runtime/'
}
];
+ let blogsCommunity = [
+ {
+ title: 'AMD expands its AI and ML development tools with ROCm 6.0',
+ date: 'February 15, 2024',
+ link: 'https://overclock3d.net/news/software/amd-expands-its-ai-and-machine-learning-development-tools-with-rocm-6-0-with-expanded-gpu-support/',
+ blurb:
+ 'ROCm 6.0 features support for the ONNX runtime. This support enhances AI development capabilities and interoperability.'
+ },
+ {
+ title: 'UC San Diego Students Win MLPerf Contest at SC23',
+ date: 'February 2, 2024',
+ blurb:
+ 'During the annual Student Cluster Competition (SCC), UC San Diego undergraduate students achieved third place. Their success was fueled by optimizing performance using industry benchmarks, including the MLPerf Inference Benchmark. The seamless support for PyTorch and ONNX Runtime enabled them to port and fine-tune their code efficiently.',
+ link: 'https://www.hpcwire.com/off-the-wire/uc-san-diego-students-win-mlperf-contest-at-sc23/'
+ },
+ {
+ title: 'Human Capital Management (HCM) - Sentence Similarity Language Model using Java',
+ date: 'December 5, 2023',
+ blurb: 'Using ONNX Runtime, the HCM team was able to deploy a sentence similarity language model using Java, demonstrating how easy it is to use with multiple languages.',
+ link: 'https://www.linkedin.com/pulse/hcm-sentence-similarity-language-model-using-java-jonathon-palmieri-tdlpc%3FtrackingId=CN2PPVO4Toqh8r6JsAYMIw%253D%253D/?trackingId=ByNomo0pQFKM%2F%2BWEknVs7Q%3D%3D'
+ }
+ ];
@@ -287,12 +322,35 @@
{/each}
-