Update README.md

README.md

@@ -69,7 +69,7 @@ language:
 - my
 - ne
 - nl
-- no
+- 'no'
 - ny
 - pa
 - pl
@@ -105,24 +105,35 @@ language:
 - yo
 - zh
 - zu
-pipeline_tag: text-generation
+pipeline_tag: text2text-generation
 widget:
-- 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？"
-  example_title: "zh-zh sentiment"
-- text: "Suggest at least five related search terms to \"Mạng neural nhân tạo\"."
-  example_title: "vi-en query"
-- text: "Proposez au moins cinq mots clés concernant «Réseau de neurones artificiels»."
-  example_title: "fr-fr query"
-- text: "Explain in a sentence in Telugu what is backpropagation in neural networks."
-  example_title: "te-en qa"
-- text: "Why is the sky blue?"
-  example_title: "en-en qa"
-- text: "Write a fairy tale about a troll saving a princess from a dangerous dragon. The fairy tale is a masterpiece that has achieved praise worldwide and its moral is \"Heroes Come in All Shapes and Sizes\". Story (in Spanish):"
-  example_title: "es-en fable"
-- text: "Write a fable about wood elves living in a forest that is suddenly invaded by ogres. The fable is a masterpiece that has achieved praise worldwide and its moral is \"Violence is the last refuge of the incompetent\". Fable (in Hindi):"
-  example_title: "hi-en fable"
+- 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？
+  example_title: zh-zh sentiment
+- text: Suggest at least five related search terms to "Mạng neural nhân tạo".
+  example_title: vi-en query
+- text: >-
+    Proposez au moins cinq mots clés concernant «Réseau de neurones
+    artificiels».
+  example_title: fr-fr query
+- text: Explain in a sentence in Telugu what is backpropagation in neural networks.
+  example_title: te-en qa
+- text: Why is the sky blue?
+  example_title: en-en qa
+- text: >-
+    Write a fairy tale about a troll saving a princess from a dangerous dragon.
+    The fairy tale is a masterpiece that has achieved praise worldwide and its
+    moral is "Heroes Come in All Shapes and Sizes". Story (in Spanish):
+  example_title: es-en fable
+- text: >-
+    Write a fable about wood elves living in a forest that is suddenly invaded
+    by ogres. The fable is a masterpiece that has achieved praise worldwide and
+    its moral is "Violence is the last refuge of the incompetent". Fable (in
+    Hindi):
+  example_title: hi-en fable
 model-index:
 - name: mt0-xl
   results:
@@ -235,7 +246,7 @@ model-index:
       revision: 9dbd830a06fea8b1c49d6e5ef2004a08d9f45094
     metrics:
     - type: Accuracy
-      value: 39.0
+      value: 39
   - task:
       type: Natural language inference
     dataset:
@@ -433,17 +444,17 @@ model-index:
       revision: e8dc562f5de170c54b5481011dd9f4fa04845771
     metrics:
     - type: Pass@1
-      value: 0.00
+      value: 0
     - type: Pass@10
-      value: 0.00
+      value: 0
     - type: Pass@100
-      value: 0.00
+      value: 0
   - task:
       type: Sentence completion
     dataset:
       type: story_cloze
       name: StoryCloze (2016)
-      config: "2016"
+      config: '2016'
       split: validation
       revision: e724c6f8cdf7c7a2fb229d862226e15b023ee4db
     metrics:
@@ -459,7 +470,7 @@ model-index:
       revision: 9e12063561e7e6c79099feb6d5a493142584e9e2
     metrics:
     - type: Accuracy
-      value: 72.0
+      value: 72
   - task:
       type: Sentence completion
     dataset:
@@ -470,7 +481,7 @@ model-index:
       revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
     metrics:
     - type: Accuracy
-      value: 70.0
+      value: 70
   - task:
       type: Sentence completion
     dataset:
@@ -481,7 +492,7 @@ model-index:
       revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
     metrics:
     - type: Accuracy
-      value: 66.0
+      value: 66
   - task:
       type: Sentence completion
     dataset:
@@ -492,7 +503,7 @@ model-index:
       revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
     metrics:
     - type: Accuracy
-      value: 71.0
+      value: 71
   - task:
       type: Sentence completion
     dataset:
@@ -503,7 +514,7 @@ model-index:
       revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
     metrics:
     - type: Accuracy
-      value: 70.0
+      value: 70
   - task:
       type: Sentence completion
     dataset:
@@ -514,7 +525,7 @@ model-index:
       revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
     metrics:
     - type: Accuracy
-      value: 56.0
+      value: 56
   - task:
       type: Sentence completion
     dataset:
@@ -525,7 +536,7 @@ model-index:
       revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
     metrics:
     - type: Accuracy
-      value: 53.0
+      value: 53
   - task:
       type: Sentence completion
     dataset:
@@ -536,7 +547,7 @@ model-index:
       revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
     metrics:
     - type: Accuracy
-      value: 64.0
+      value: 64
   - task:
       type: Sentence completion
     dataset:
@@ -547,7 +558,7 @@ model-index:
       revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
     metrics:
     - type: Accuracy
-      value: 60.0
+      value: 60
   - task:
       type: Sentence completion
     dataset:
@@ -558,7 +569,7 @@ model-index:
       revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
     metrics:
     - type: Accuracy
-      value: 58.0
+      value: 58
   - task:
       type: Sentence completion
     dataset:
@@ -569,7 +580,7 @@ model-index:
       revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
     metrics:
     - type: Accuracy
-      value: 68.0
+      value: 68
   - task:
       type: Sentence completion
     dataset:
@@ -580,7 +591,7 @@ model-index:
       revision: 37f73c60fb123111fa5af5f9b705d0b3747fd187
     metrics:
     - type: Accuracy
-      value: 65.0
+      value: 65
   - task:
       type: Sentence completion
     dataset: