added NeMo curator

rapidsai · Jun 5, 2024 · 64b1981 · 64b1981
1 parent ee6eb31
commit 64b1981
Showing 1 changed file with 31 additions and 11 deletions.
diff --git a/layouts/page/ecosystem.html b/layouts/page/ecosystem.html
@@ -390,19 +390,19 @@ <h2><i class="fa-regular fa-gauge-circle-bolt"></i> Triton </h2>
               class="fa-solid fa-arrow-up-right"></i> </a>
         </div>
         <div class="col-md-6 py-3">
-          <h2><i class="fa-regular fa-gauge-circle-bolt"></i> Merlin </h2>
+          <h2><i class="fa-regular fa-gauge-circle-bolt"></i> NeMo Curator </h2>
           <div class="tags-container border-top border-2 border-rapids-purple-primary">
             <span class="tags-item text-rapids-purple-primary border-rapids-purple-primary"><i
-                class="fa-solid fa-tag"></i> RECOMMENDERS </span>
+              class="fa-solid fa-tag"></i> CURATION </span>
             <span class="tags-item text-rapids-purple-primary border-rapids-purple-primary"><i
-                class="fa-solid fa-tag"></i> NVIDIA AI </span>
+                class="fa-solid fa-tag"></i> PYTHON </span>
+            <span class="tags-item text-rapids-purple-primary border-rapids-purple-primary"><i
+                class="fa-solid fa-tag"></i> NeMo</span>
           </div>
-          <p> NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems. Merlin
-            leverages RAPIDS cuDF and Dask cuDF for dataframe transformation during ETL and inference, as well as for
-            the optimized dataloaders in TensorFlow, PyTorch or HugeCTR to accelerate deep learning training. </p>
-          <a href="https://github.com/NVIDIA-Merlin" target="_blank">GitHub <i class="fa-solid fa-arrow-up-right"></i>
+          <p> NeMo Curator is a Python library designed for scalable and efficient dataset preparation, enhancing LLM training accuracy through GPU-accelerated data curation using Dask and RAPIDS. It offers a customizable and modular interface that simplifies pipeline expansion and accelerates model convergence by preparing high-quality tokens. </p>
+          <a href="https://github.com/NVIDIA/NeMo-Curator" target="_blank">GitHub <i class="fa-solid fa-arrow-up-right"></i>
           </a> <br>
-          <a href="https://developer.nvidia.com/nvidia-merlin" target="_blank">Learn More <i
+          <a href="https://docs.nvidia.com/nemo-framework/user-guide/latest/datacuration/index.html" target="_blank">Learn More <i
               class="fa-solid fa-arrow-up-right"></i> </a>
         </div>
       </div>
@@ -470,6 +470,27 @@ <h2><i class="fa-regular fa-gauge-circle-bolt"></i> Monai </h2>
           <a href="https://monai.io/" target="_blank">Project Page <i class="fa-solid fa-arrow-up-right"></i> </a>
         </div>
       </div>
+      <div class="row">
+        <div class="col-md-6 py-3">
+          <h2><i class="fa-regular fa-gauge-circle-bolt"></i> Merlin </h2>
+          <div class="tags-container border-top border-2 border-rapids-purple-primary">
+            <span class="tags-item text-rapids-purple-primary border-rapids-purple-primary"><i
+                class="fa-solid fa-tag"></i> RECOMMENDERS </span>
+            <span class="tags-item text-rapids-purple-primary border-rapids-purple-primary"><i
+                class="fa-solid fa-tag"></i> NVIDIA AI </span>
+          </div>
+          <p> NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems. Merlin
+            leverages RAPIDS cuDF and Dask cuDF for dataframe transformation during ETL and inference, as well as for
+            the optimized dataloaders in TensorFlow, PyTorch or HugeCTR to accelerate deep learning training. </p>
+          <a href="https://github.com/NVIDIA-Merlin" target="_blank">GitHub <i class="fa-solid fa-arrow-up-right"></i>
+          </a> <br>
+          <a href="https://developer.nvidia.com/nvidia-merlin" target="_blank">Learn More <i
+              class="fa-solid fa-arrow-up-right"></i> </a>
+        </div>
+        <div class="col-md-6 py-3">
+
+        </div>
+      </div>
     </div>
   </div>
 </section>
@@ -496,8 +517,7 @@ <h2><i class="fa-regular fa-split"></i> Data Science Workflows </h2>
         <div class="col-md-6 py-3">
           <h2><i class="fa-regular fa-panel-fire"></i> MLOps Guides</h2>
           <p>Deploy and maintain RAPIDS in production environments with these machine learning operations, hyper
-            parameter optimization, and integration guides on our <a
-              href="https://github.com/rapidsai/cloud-ml-examples" target="_blank">Cloud ML Examples Repository</a> and
+            parameter optimization, and integration guides on our
             <a href="https://docs.rapids.ai/deployment/stable/" target="_blank">Deployments Page <i
                 class="fa-solid fa-arrow-up-right"></i></a> </p>
         </div>
@@ -526,7 +546,7 @@ <h2><i class="fa-regular fa-chalkboard-user"></i> Maintainer Guides </h2>
               target="_blank"> Maintainer Documentation Page <i class="fa-solid fa-arrow-up-right"></i> </a> </p>
         </div>
         <div class="col-md-6 py-3">
-          <h2><i class="fa-regular fa-code-pull-request"></i>Contribution Guides </h2>
+          <h2><i class="fa-regular fa-code-pull-request"></i> Contribution Guides </h2>
           <p>Open source projects stay healthy with active contributions. Overall contribution guides can be found on
             our <a href="https://docs.rapids.ai/contributing" target="_blank">Documentation</a>. Each RAPIDS repository
             also has helpful and