First draft Organization card

README.md

@@ -8,38 +8,41 @@ pinned: false
 license: apache-2.0
 ---
 
-# Configuration
-
-`title`: _string_
-Display title for the Space
-
-`emoji`: _string_
-Space emoji (emoji-only character allowed)
-
-`colorFrom`: _string_
-Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
-
-`colorTo`: _string_
-Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
-
-`sdk`: _string_
-Can be either `gradio`, `streamlit`, or `static`
-
-`sdk_version` : _string_
-Only applicable for `streamlit` SDK.  
-See [doc](https://hf.co/docs/hub/spaces) for more info on supported versions.
-
-`app_file`: _string_
-Path to your main application file (which contains either `gradio` or `streamlit` Python code, or `static` html code).
-Path is relative to the root of the repository.
-
-`models`: _List[string]_
-HF model IDs (like "gpt2" or "deepset/roberta-base-squad2") used in the Space.
-Will be parsed automatically from your code if not specified here.
-
-`datasets`: _List[string]_
-HF dataset IDs (like "common_voice" or "oscar-corpus/OSCAR-2109") used in the Space.
-Will be parsed automatically from your code if not specified here.
-
-`pinned`: _boolean_
-Whether the Space stays on top of your list.
+<p class="lg:col-span-3">
+	Graphcore and Hugging Face are working together to make training of Transformer models on IPUs fast and easy. <a href="https://www.graphcore.ai/hugging-face-hardware">Contact Graphcore</a> to learn more about leveraging IPUs for your training needs.
+</p>
+<a href="https://huggingface.co/blog/graphcore" class="block overflow-hidden group">
+	<img
+		alt=""
+		src="front/assets/graphcore-page/hero-shot-graphcore-huggingface.png"
+		class="w-full h-40 object-cover mb-2 bg-gray-300 rounded-lg"
+	/>
+	<div class="underline">Learn more about our partnership with Hugging Face</div>
+</a>
+<a href="https://github.com/huggingface/optimum-graphcore" class="block overflow-hidden">
+	<img
+		alt=""
+		src="/blog/assets/38_getting_started_graphcore/graphcore_1.png"
+		class="w-full h-40 object-cover mb-2 bg-gray-300 rounded-lg"
+	/>
+	<div class="underline">Check out Optimum Graphcore library</div>
+</a>
+<a href="https://www.graphcore.ai/developer" class="block overflow-hidden group">
+    <img
+        alt=""
+        src="/front/assets/graphcore-page/poplar-software.png"
+        class="w-full h-40 object-cover mb-2 bg-gray-300 rounded-lg"
+    />
+	<div class="underline">Discover Graphcore developer tools</div>
+</a>
+<div class="lg:col-span-3">
+	<p class="mb-2">
+        Accelerate training and inference models with high-performance optimisations across natural language processing, computer vision and more.
+	</p>
+	<p class="mb-2">
+        Graphcore’s IPU is powering advances in AI applications such as fraud detection for finance, drug discovery for life sciences, defect detection for manufacturing, traffic monitoring for smart cities and for all of tomorrow’s new breakthroughs.
+	</p>
+	<p>
+		Learn more at <a href="/graphcore" class="underline">hf.co/graphcore</a>
+	</p>
+</div>