Update README.md

README.md

@@ -108,12 +108,49 @@ language:
 tags:
 - text2text-generation
 widget:
+- text: "<table>
+  <tr>
+<th>Name</th>
+<th>Explanation</th>
+<th>Example models</th>
+</tr>
+<tr>
+<td><a href=https://huggingface.co/datasets/bigscience/xP3>xP3</a></t> 
+<td>Mixture of 13 training tasks in 46 languages with English prompts</td>
+<td><a href=https://huggingface.co/bigscience/bloomz>bloomz</a> & <a href=https://huggingface.co/bigscience/mt0-xxl>mt0-xxl</a></td>
+</tr>
+<tr>
+<td><a href=https://huggingface.co/datasets/bigscience/xP3mt>xP3mt</a></t> 
+<td>Mixture of 13 training tasks in 46 languages with prompts in 20 languages (machine-translated from English)</td>
+<td><a href=https://huggingface.co/bigscience/bloomz-mt>bloomz-mt</a> & <a href=https://huggingface.co/bigscience/mt0-xxl-mt>mt0-xxl-mt</a></td>
+</tr>
+<tr>
+<td><a href=https://huggingface.co/datasets/bigscience/xP3all>xP3all</a></t> 
+<td>xP3 + our evaluation datasets adding an additional 3 tasks for a total of 16 tasks in 46 languages with English prompts</td>
+<td></td>
+</tr>
+<tr>
+<td><a href=https://huggingface.co/datasets/bigscience/xP3megds>xP3megds</a></t> 
+<td><a href=https://github.com/bigscience-workshop/Megatron-DeepSpeed>Megatron-DeepSpeed</a> processed version of xP3</td>
+<td><a href=https://huggingface.co/bigscience/bloomz>bloomz</a></td>
+</tr>
+<tr>
+<td><a href=https://huggingface.co/datasets/Muennighoff/P3>P3</a></t> 
+<td>Repreprocessed version of the English-only <a href=https://huggingface.co/datasets/bigscience/P3>P3</a> with 8 training tasks</td>
+<td><a href=https://huggingface.co/bigscience/bloomz-p3>bloomz-p3</a> & <a href=https://huggingface.co/bigscience/mt0-xxl-p3>mt0-xxl-p3</a></td>
+</tr>
+</table>
+Which dataset has the most tasks?"
+  example_title: "en-en struct-to-text"
 - text: "Life is beautiful! Translate to Mongolian."
   example_title: "mn-en translation"
 - text: "Le mot japonais «憂鬱» veut dire quoi en Odia?"
   example_title: "jp-or-fr translation"
 - text: "Stell mir eine schwierige Quiz Frage bei der es um Astronomie geht. Bitte stell die Frage auf Norwegisch."
   example_title: "de-nb quiz"
+- text: "We present BLOOMZ & mT0, a family of models capable of following human instructions in dozens of languages zero-shot. We finetune BLOOM & mT5 pretrained multilingual language models on our crosslingual task mixture (xP3) and find our resulting models capable of crosslingual generalization to unseen tasks & languages.
+What are the keywords in Chinese?"
+  example_title: "zh-en keywords"  
 - text: "一个传奇的开端，一个不灭的神话，这不仅仅是一部电影，而是作为一个走进新时代的标签，永远彪炳史册。Would you rate the previous review as positive, neutral or negative?"
   example_title: "zh-en sentiment"
 - text: "一个传奇的开端，一个不灭的神话，这不仅仅是一部电影，而是作为一个走进新时代的标签，永远彪炳史册。你认为这句话的立场是赞扬、中立还是批评？"