Merge branch 'master' of https://github.com/explosion/spaCy

.github/CONTRIBUTOR_AGREEMENT.md

@@ -101,6 +101,6 @@ mark both statements:
 | Name                           | Abhinav Sharma                     |
 | Company name (if applicable)   | Fourtek I.T. Solutions Pvt. Ltd.   |
 | Title or role (if applicable)  | Machine Learning Engineer          |
-| Date                           | 3 Novermber 2017                   |
+| Date                           | 3 November 2017                   |
 | GitHub username                | abhi18av                           |
 | Website (optional)             | https://abhi18av.github.io/        |

spacy/lang/hi/examples.py

@@ -0,0 +1,22 @@
+  # coding: utf8
+from __future__ import unicode_literals
+
+
+"""
+Example sentences to test spaCy and its language models.
+
+>>> from spacy.lang.hi.examples import sentences
+>>> docs = nlp.pipe(sentences)
+"""
+
+
+sentences = [
+     "एप्पल 1 अरब डॉलर के लिए यू.के. स्टार्टअप खरीदने पर विचार कर रहा है",
+     "स्वायत्त कार निर्माताओं की ओर बीमा दायित्व रखती है",
+     "सैन फ्रांसिस्को फुटवे डिलीवरी रोबोटों पर प्रतिबंध लगाने का विचार कर रहा है",
+     "लंदन यूनाइटेड किंगडम का बड़ा शहर है।",
+     "आप कहाँ हैं?",
+     "फ्रांस के राष्ट्रपति कौन हैं?",
+     "संयुक्त राज्य की राजधानी क्या है?",
+     "बराक ओबामा का जन्म हुआ था?"
+]

website/_harp.json

@@ -83,7 +83,7 @@
         ],
 
         "V_CSS": "2.0.0",
-        "V_JS": "2.0.0",
+        "V_JS": "2.0.1",
         "DEFAULT_SYNTAX": "python",
         "ANALYTICS": "UA-58931649-1",
         "MAILCHIMP": {

website/assets/js/models.js

@@ -141,7 +141,6 @@ export class ModelLoader {
         if (!accuracy && !speed) return;
         this.renderTable(tpl, 'parser', accuracy, val => val.toFixed(2));
         this.renderTable(tpl, 'ner', accuracy, val => val.toFixed(2));
-        this.renderTable(tpl, 'speed', speed, Math.round);
         tpl.get('benchmarks').hidden = false;
     }
 
@@ -327,7 +326,6 @@ export class ModelComparer {
         const allKeys = [].concat(...Object.entries(this.benchKeys).map(([_, v]) => Object.keys(v)));
         for (let key of allKeys) {
             if (accuracy[key]) this.tpl.fill(`${key}${i}`, accuracy[key].toFixed(2))
-            else if (speed[key]) this.tpl.fill(`${key}${i}`, convertNumber(Math.round(speed[key])))
             else this.tpl.fill(`${key}${i}`, 'n/a')
         }
     }

website/models/_data.json

@@ -40,7 +40,7 @@
     },
 
     "MODELS": {
-        "en": ["en_core_web_sm", "en_core_web_lg", "en_vectors_web_lg"],
+        "en": ["en_core_web_sm", "en_core_web_md", "en_core_web_lg", "en_vectors_web_lg"],
         "de": ["de_core_news_sm"],
         "es": ["es_core_news_sm", "es_core_news_md"],
         "pt": ["pt_core_news_sm"],
@@ -86,8 +86,7 @@
 
     "MODEL_BENCHMARKS": {
         "parser": { "uas": "UAS", "las": "LAS", "tags_acc": "POS" },
-        "ner":    { "ents_f": "NER F", "ents_p": "NER P", "ents_r": "NER R" },
-        "speed":  { "nwords": "Words", "cpu": "w/s CPU", "gpu": "w/s GPU" }
+        "ner":    { "ents_f": "NER F", "ents_p": "NER P", "ents_r": "NER R" }
     },
 
     "LANGUAGES": {

website/usage/_facts-figures/_benchmarks-models.jade

@@ -19,18 +19,28 @@ p
 +table(["Model", "spaCy", "Type", "UAS", "NER F", "POS", "WPS", "Size"])
     +row
         +cell #[+a("/models/en#en_core_web_sm") #[code en_core_web_sm]] 2.0.0
-        each data in ["2.x", "neural"]
-            +cell("num")=data
+        +cell("num") 2.x
+        +cell neural
         +cell("num") 91.7
         +cell("num") 85.3
         +cell("num") 97.0
         +cell("num") 10.1k
         +cell("num") #[strong 35MB]
 
+    +row
+        +cell #[+a("/models/en#en_core_web_md") #[code en_core_web_md]] 2.0.0
+        +cell("num") 2.x
+        +cell neural
+        +cell("num") 91.7
+        +cell("num") #[strong 85.9]
+        +cell("num") 97.1
+        +cell("num") 10.0k
+        +cell("num") 115MB
+
     +row
         +cell #[+a("/models/en#en_core_web_lg") #[code en_core_web_lg]] 2.0.0
-        each data in ["2.x", "neural"]
-            +cell("num")=data
+        +cell("num") 2.x
+        +cell neural
         +cell("num") #[strong 91.9]
         +cell("num") #[strong 85.9]
         +cell("num") #[strong 97.2]
@@ -39,15 +49,23 @@ p
 
     +row("divider")
         +cell #[code en_core_web_sm] 1.2.0
-        each data in ["1.x", "linear", 86.6, 78.5, 96.6]
-            +cell("num")=data
+        +cell("num") 1.x
+        +cell linear
+        +cell("num") 86.6
+        +cell("num") 78.5
+        +cell("num") 96.6
         +cell("num") #[strong 25.7k]
         +cell("num") 50MB
 
     +row
         +cell #[code en_core_web_md] 1.2.1
-        each data in ["1.x", "linear", 90.6, 81.4, 96.7, "18.8k", "1GB"]
-            +cell("num")=data
+        +cell("num") 1.x
+        +cell linear
+        +cell("num") 90.6
+        +cell("num") 81.4
+        +cell("num") 96.7
+        +cell("num") 18.8k
+        +cell("num") 1GB
 
 +h(4, "benchmarks-models-spanish") Spanish
 

website/usage/_install/_instructions.jade

@@ -31,10 +31,8 @@ p
     +badge("https://anaconda.org/conda-forge/spacy/badges/version.svg", "https://anaconda.org/conda-forge/spacy")
 
 +infobox("Important note", "⚠️")
-    |  We're still waiting for spaCy v2.0 to
-    |  #[+a("https://github.com/conda-forge/spacy-feedstock/pulls") go live]
-    |  on #[code conda-forge], as there's currently a significant
-    |  #[+a("https://www.traviscistatus.com/") backlog] of OSX builds on Travis.
+    |  We're still waiting for spaCy v2.0 to go live on #[code conda-forge],
+    |  as there's currently a backlog of OSX builds on Travis.
     |  In the meantime, you can already try out the new version using pip. The
     |  conda download will follow as soon as possible.