Update v2 details

website/index.jade

@@ -111,8 +111,8 @@ include _includes/_mixins
         |  deliver accuracy in-line with the latest research systems,
         |  even when  evaluated from raw text. With these innovations, spaCy
         |  v2.0's models are #[strong 10× smaller],
-        |  #[strong 20% more accurate], and #[strong just as fast] as the
-        |  previous generation.
+        |  #[strong 20% more accurate], and #[strong even cheaper to run] than
+        |  the previous generation.
 
     .o-block-small.u-text-right
         +button("/models", true, "secondary-light") Download models

website/models/index.jade

@@ -20,8 +20,8 @@ include ../_includes/_mixins
         |  deliver #[strong accuracy in-line with the latest research systems],
         |  even when  evaluated from raw text. With these innovations, spaCy
         |  v2.0's models are #[strong 10× smaller],
-        |  #[strong 20% more accurate], and #[strong just as fast] as the
-        |  previous generation.
+        |  #[strong 20% more accurate], and #[strong even cheaper to run] than
+        |  the previous generation.
 
     include ../usage/_models/_quickstart
 

website/usage/_install/_instructions.jade

@@ -91,7 +91,7 @@ p
     |  As of v2.0, spaCy's comes with neural network models that are implemented
     |  in our machine learning library, #[+a(gh("thinc")) Thinc]. For GPU
     |  support, we've been grateful to use the work of
-    |  #[+a("http://chainer.org") Chainer]'s CuPy module, which provides
+    |  Chainer's #[+a("https://cupy.chainer.org") CuPy] module, which provides
     |  a NumPy-compatible interface for GPU arrays.
 
 p

website/usage/_v2/_features.jade

@@ -10,8 +10,9 @@ p
 +h(3, "features-models") Convolutional neural network models
 
 +aside-code("Example", "bash")
-    for model in ["en", "de", "fr", "es", "pt", "it"]
-        | spacy download #{model}  # default #{LANGUAGES[model]} model!{'\n'}
+    for _, lang in MODELS
+        if lang != "xx"
+            | spacy download #{lang}  # default #{LANGUAGES[lang]} model!{'\n'}
     | spacy download xx_ent_wiki_sm  # multi-language NER
 
 p
@@ -20,14 +21,22 @@ p
     |  been designed and implemented from scratch specifically for spaCy, to
     |  give you an unmatched balance of speed, size and accuracy. The new
     |  models are #[strong 10× smaller], #[strong 20% more accurate],
-    |  and #[strong just as fast] as the previous generation.
-    |  #[strong GPU usage] is now supported via
-    |  #[+a("http://chainer.org") Chainer]'s CuPy module.
+    |  and #[strong even cheaper to run] than the previous generation.
+
+p
+    |  spaCy v2.0's new neural network models bring significant improvements in
+    |  accuracy, especially for English Named Entity Recognition. The new
+    |  #[+a("/models/en#en_core_web_lg") #[code en_core_web_lg]] model makes
+    |  about #[strong 25% fewer mistakes] than the corresponding v1.x model and
+    |  is within #[strong 1% of the current state-of-the-art]
+    |  (#[+a("https://arxiv.org/pdf/1702.02098.pdf") Strubell et al., 2017]).
+    |  The v2.0 models are also cheaper to run at scale, as they require
+    |  #[strong under 1 GB of memory] per process.
 
 +infobox
     |  #[+label-inline Usage:] #[+a("/models") Models directory],
     |  #[+a("/models/comparison") Models comparison],
-    |  #[+a("/usage/#gpu") Using spaCy with GPU]
+    |  #[+a("#benchmarks") Benchmarks]
 
 +h(3, "features-pipelines") Improved processing pipelines
 

website/usage/_v2/_summary.jade

@@ -22,7 +22,7 @@ p
             |  #[strong deep learning-powered models] for spaCy's tagger,
             |  parser and entity recognizer. The new models are
             |  #[strong 10× smaller], #[strong 20% more accurate] and
-            |  just as fast as the previous generation.
+            |  #[strong even cheaper to run] than the previous generation.
 
         p
             |  We've also made several usability improvements that are

website/usage/models.jade

@@ -3,7 +3,7 @@
 include ../_includes/_mixins
 
 p
-    |  As of v1.7.0, models for spaCy can be installed as #[strong Python packages].
+    |  spaCy's models can be installed as #[strong Python packages].
     |  This means that they're a component of your application, just like any
     |  other module. They're versioned and can be defined as a dependency in your
     |  #[code requirements.txt]. Models can be installed from a download URL or