Merge branch 'master' of https://github.com/explosion/spacy-models

explosion · Feb 7, 2019 · 0923175 · 0923175
2 parents 9609fbe + 6abb7b7
commit 0923175
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diff --git a/compatibility.json b/compatibility.json
@@ -464,23 +464,41 @@
             "de_core_news_md": ["1.0.0"],
             "en_vectors_glove_md": ["1.0.0"]
         },
+        "2.1.0a7": {
+            "en_vectors_web_lg": ["2.0.0"],
+            "en_core_web_sm": ["2.1.0a7"],
+            "en_core_web_md": ["2.1.0a7"],
+            "en_core_web_lg": ["2.1.0a7"],
+            "de_core_news_sm": ["2.1.0a7"],
+            "de_core_news_md": ["2.1.0a7"],
+            "es_core_news_sm": ["2.1.0a7"],
+            "es_core_news_md": ["2.1.0a7"],
+            "pt_core_news_sm": ["2.1.0a7"],
+            "fr_core_news_sm": ["2.1.0a7"],
+            "fr_core_news_md": ["2.1.0a7"],
+            "el_core_news_sm": ["2.1.0a7"],
+            "el_core_news_md": ["2.1.0a7"],
+            "it_core_news_sm": ["2.1.0a7"],
+            "nl_core_news_sm": ["2.1.0a7"],
+            "xx_ent_wiki_sm": ["2.1.0a7"]
+        },
         "2.1.0a6": {
             "en_vectors_web_lg": ["2.0.0"],
-            "en_core_web_sm": ["2.1.0a5"],
-            "en_core_web_md": ["2.1.0a5"],
-            "en_core_web_lg": ["2.1.0a5"],
-            "de_core_news_sm": ["2.1.0a5"],
-            "de_core_news_md": ["2.1.0a5"],
-            "es_core_news_sm": ["2.1.0a5"],
-            "es_core_news_md": ["2.1.0a5"],
-            "pt_core_news_sm": ["2.1.0a5"],
-            "fr_core_news_sm": ["2.1.0a5"],
-            "fr_core_news_md": ["2.1.0a5"],
-            "el_core_news_sm": ["2.1.0a5"],
-            "el_core_news_md": ["2.1.0a5"],
-            "it_core_news_sm": ["2.1.0a5"],
-            "nl_core_news_sm": ["2.1.0a5"],
-            "xx_ent_wiki_sm": ["2.1.0a5"]
+            "en_core_web_sm": ["2.1.0a5", "2.1.0a6"],
+            "en_core_web_md": ["2.1.0a5", "2.1.0a6"],
+            "en_core_web_lg": ["2.1.0a5", "2.1.0a6"],
+            "de_core_news_sm": ["2.1.0a5", "2.1.0a6"],
+            "de_core_news_md": ["2.1.0a5", "2.1.0a6"],
+            "es_core_news_sm": ["2.1.0a5", "2.1.0a6"],
+            "es_core_news_md": ["2.1.0a5", "2.1.0a6"],
+            "pt_core_news_sm": ["2.1.0a5", "2.1.0a6"],
+            "fr_core_news_sm": ["2.1.0a5", "2.1.0a6"],
+            "fr_core_news_md": ["2.1.0a5", "2.1.0a6"],
+            "el_core_news_sm": ["2.1.0a5", "2.1.0a6"],
+            "el_core_news_md": ["2.1.0a5", "2.1.0a6"],
+            "it_core_news_sm": ["2.1.0a5", "2.1.0a6"],
+            "nl_core_news_sm": ["2.1.0a5", "2.1.0a6"],
+            "xx_ent_wiki_sm": ["2.1.0a5", "2.1.0a6"]
         },
         "2.1.0a5": {
             "en_vectors_web_lg": ["2.0.0"],

diff --git a/meta/de_core_news_md-2.1.0a6.json b/meta/de_core_news_md-2.1.0a6.json
@@ -0,0 +1,44 @@
+{
+  "accuracy": {
+    "ents_f": 83.8971731371,
+    "ents_p": 84.725523799,
+    "ents_r": 83.084863007,
+    "las": 90.3313400502,
+    "tags_acc": 97.4595722142,
+    "token_acc": 99.4792618308,
+    "uas": 92.1905835918
+  },
+  "author": "Explosion AI",
+  "description": "German multi-task CNN trained on the TIGER and WikiNER corpus. Assigns context-specific token vectors, POS tags, dependency parse and named entities. Supports identification of PER, LOC, ORG and MISC entities.",
+  "email": "[email protected]",
+  "lang": "de",
+  "license": "MIT",
+  "name": "core_news_md",
+  "notes": "Because the model is trained on Wikipedia, it may perform inconsistently on many genres, such as social media text. The NER accuracy refers to the \"silver standard\" annotations in the WikiNER corpus. Accuracy on these annotations tends to be higher than correct human annotations.",
+  "parent_package": "spacy-nightly",
+  "pipeline": [
+    "tagger",
+    "parser",
+    "ner"
+  ],
+  "sources": [
+    "TIGER Corpus",
+    "Wikipedia"
+  ],
+  "spacy_version": ">=2.1.0a4",
+  "speed": {
+    "cpu": 6860.2096209861,
+    "gpu": null,
+    "nwords": 696811
+  },
+  "url": "https://explosion.ai",
+  "vectors": {
+    "keys": 276087,
+    "name": "de_model.vectors",
+    "vectors": 20000,
+    "width": 300
+  },
+  "version": "2.1.0a6",
+  "size": "210 MB",
+  "checksum": "4338d30cbf5f8c2c25d05e2d830d5d2783024c16f436fabcb397b61fa3a40a92"
+}
diff --git a/meta/de_core_news_sm-2.1.0a6.json b/meta/de_core_news_sm-2.1.0a6.json
@@ -0,0 +1,38 @@
+{
+  "accuracy": {
+    "ents_f": 83.3361633136,
+    "ents_p": 84.2093028404,
+    "ents_r": 82.4809445848,
+    "las": 89.5520616147,
+    "tags_acc": 97.2045485755,
+    "token_acc": 99.4792618308,
+    "uas": 91.623693173
+  },
+  "author": "Explosion AI",
+  "description": "German multi-task CNN trained on the TIGER and WikiNER corpus. Assigns context-specific token vectors, POS tags, dependency parse and named entities. Supports identification of PER, LOC, ORG and MISC entities.",
+  "email": "[email protected]",
+  "lang": "de",
+  "license": "MIT",
+  "name": "core_news_sm",
+  "notes": "Because the model is trained on Wikipedia, it may perform inconsistently on many genres, such as social media text. The NER accuracy refers to the \"silver standard\" annotations in the WikiNER corpus. Accuracy on these annotations tends to be higher than correct human annotations.",
+  "parent_package": "spacy-nightly",
+  "pipeline": [
+    "tagger",
+    "parser",
+    "ner"
+  ],
+  "sources": [
+    "TIGER Corpus",
+    "Wikipedia"
+  ],
+  "spacy_version": ">=2.1.0a4",
+  "speed": {
+    "cpu": 7351.1354011755,
+    "gpu": null,
+    "nwords": 696811
+  },
+  "url": "https://explosion.ai",
+  "version": "2.1.0a6",
+  "size": "10 MB",
+  "checksum": "60c70639a46b0888154815ebb932bbfe3366134be41b959b62047698bd654f45"
+}
diff --git a/meta/el_core_news_md-2.1.0a6.json b/meta/el_core_news_md-2.1.0a6.json
@@ -0,0 +1,44 @@
+{
+  "accuracy": {
+    "ents_f": 81.0020876827,
+    "ents_p": 80.4979253112,
+    "ents_r": 81.512605042,
+    "las": 85.1989785061,
+    "tags_acc": 96.5910179067,
+    "token_acc": 100.0,
+    "uas": 88.3592253671
+  },
+  "author": "Giannis Daras",
+  "description": "Greek pipeline with word vectors, POS tags, dependencies and named entities. Word vectors use Facebook's FastText Common Crawl vectors, pruned to a vocabulary of 20,000 items. Words outside the most frequent were mapped to the nearest neighbouring vector within the 20,000 rows retained. Syntax (dependencies and POS tags) trained from the Universal Dependencies conversion of the Greek Dependency Treebank (v2.2). Named entity annotations were created by Giannis Daras using Prodigy, using the OntoNotes 5 annotation schema.",
+  "email": "[email protected]",
+  "lang": "el",
+  "license": "CC BY-NC 4.0",
+  "name": "core_news_md",
+  "parent_package": "spacy-nightly",
+  "pipeline": [
+    "tagger",
+    "parser",
+    "ner"
+  ],
+  "sources": [
+    "Common Crawl",
+    "Greek Dependency Treebank",
+    "Daras GSOC 2018"
+  ],
+  "spacy_version": ">=2.1.0a4",
+  "speed": {
+    "cpu": 7654.0669709891,
+    "gpu": null,
+    "nwords": 6191
+  },
+  "url": "https://github.com/eellak/gsoc2018-spacy",
+  "vectors": {
+    "keys": 1999938,
+    "name": "el_model.vectors",
+    "vectors": 20000,
+    "width": 300
+  },
+  "version": "2.1.0a6",
+  "size": "126 MB",
+  "checksum": "bbbc474cc51dec46018abf06f6b8b61f3f35756d389fee8053bb533e1ec610ee"
+}
diff --git a/meta/el_core_news_sm-2.1.0a6.json b/meta/el_core_news_sm-2.1.0a6.json
@@ -0,0 +1,37 @@
+{
+  "accuracy": {
+    "ents_f": 73.1006160164,
+    "ents_p": 71.4859437751,
+    "ents_r": 74.7899159664,
+    "las": 81.4743896601,
+    "tags_acc": 94.7716173513,
+    "token_acc": 100.0,
+    "uas": 84.9742034998
+  },
+  "author": "Giannis Daras",
+  "description": "Greek pipeline with word vectors, POS tags, dependencies and named entities. Word vectors use Facebook's FastText Common Crawl vectors, pruned to a vocabulary of 20,000 items. Words outside the most frequent were mapped to the nearest neighbouring vector within the 20,000 rows retained. Syntax (dependencies and POS tags) trained from the Universal Dependencies conversion of the Greek Dependency Treebank (v2.2). Named entity annotations were created by Giannis Daras using Prodigy, using the OntoNotes 5 annotation schema.",
+  "email": "[email protected]",
+  "lang": "el",
+  "license": "CC BY-NC 4.0",
+  "name": "core_news_sm",
+  "parent_package": "spacy-nightly",
+  "pipeline": [
+    "tagger",
+    "parser",
+    "ner"
+  ],
+  "sources": [
+    "Greek Dependency Treebank",
+    "Daras GSOC 2018"
+  ],
+  "spacy_version": ">=2.1.0a4",
+  "speed": {
+    "cpu": 8658.590425769,
+    "gpu": null,
+    "nwords": 6191
+  },
+  "url": "https://github.com/eellak/gsoc2018-spacy",
+  "version": "2.1.0a6",
+  "size": "10 MB",
+  "checksum": "4ca49e6fafabff31df82e53df79f545f6bf78b12fa22146e867ce757aeb55ee4"
+}
diff --git a/meta/en_core_web_lg-2.1.0a6.json b/meta/en_core_web_lg-2.1.0a6.json
@@ -0,0 +1,43 @@
+{
+  "accuracy": {
+    "ents_f": 86.6234201991,
+    "ents_p": 86.6767388507,
+    "ents_r": 86.5701671045,
+    "las": 90.2009214654,
+    "tags_acc": 97.0161369547,
+    "token_acc": 99.0646795541,
+    "uas": 91.9664476128
+  },
+  "author": "Explosion AI",
+  "description": "English multi-task CNN trained on OntoNotes, with GloVe vectors trained on Common Crawl. Assigns word vectors, context-specific token vectors, POS tags, dependency parse and named entities.",
+  "email": "[email protected]",
+  "lang": "en",
+  "license": "MIT",
+  "name": "core_web_lg",
+  "parent_package": "spacy-nightly",
+  "pipeline": [
+    "tagger",
+    "parser",
+    "ner"
+  ],
+  "sources": [
+    "OntoNotes 5",
+    "Common Crawl"
+  ],
+  "spacy_version": ">=2.1.0a4",
+  "speed": {
+    "cpu": 7064.0263326354,
+    "gpu": null,
+    "nwords": 291344
+  },
+  "url": "https://explosion.ai",
+  "vectors": {
+    "keys": 684830,
+    "name": "en_model.vectors",
+    "vectors": 684831,
+    "width": 300
+  },
+  "version": "2.1.0a6",
+  "size": "788 MB",
+  "checksum": "6ee2325f253b8f74693c07311071eab99e504acfc37f8da7a6a88a53fb0496f9"
+}
diff --git a/meta/en_core_web_md-2.1.0a6.json b/meta/en_core_web_md-2.1.0a6.json
@@ -0,0 +1,43 @@
+{
+  "accuracy": {
+    "ents_f": 86.403312444,
+    "ents_p": 86.5049577055,
+    "ents_r": 86.3019057732,
+    "las": 90.1602551636,
+    "tags_acc": 96.9558151118,
+    "token_acc": 99.0646795541,
+    "uas": 91.9405655607
+  },
+  "author": "Explosion AI",
+  "description": "English multi-task CNN trained on OntoNotes, with GloVe vectors trained on Common Crawl. Assigns word vectors, context-specific token vectors, POS tags, dependency parse and named entities.",
+  "email": "[email protected]",
+  "lang": "en",
+  "license": "MIT",
+  "name": "core_web_md",
+  "parent_package": "spacy-nightly",
+  "pipeline": [
+    "tagger",
+    "parser",
+    "ner"
+  ],
+  "sources": [
+    "OntoNotes 5",
+    "Common Crawl"
+  ],
+  "spacy_version": ">=2.1.0a4",
+  "speed": {
+    "cpu": 7641.3076324931,
+    "gpu": null,
+    "nwords": 291344
+  },
+  "url": "https://explosion.ai",
+  "vectors": {
+    "keys": 684830,
+    "name": "en_model.vectors",
+    "vectors": 20000,
+    "width": 300
+  },
+  "version": "2.1.0a6",
+  "size": "91 MB",
+  "checksum": "ea971369a13056cee2bddaaf1c5b342b16bc0a0f45228abde4b4c4635f469f1f"
+}
diff --git a/meta/en_core_web_sm-2.1.0a6.json b/meta/en_core_web_sm-2.1.0a6.json
@@ -0,0 +1,36 @@
+{
+  "accuracy": {
+    "ents_f": 85.494302433,
+    "ents_p": 85.6597845601,
+    "ents_r": 85.3294584474,
+    "las": 89.6400460442,
+    "tags_acc": 96.7982889278,
+    "token_acc": 99.0646795541,
+    "uas": 91.5273154342
+  },
+  "author": "Explosion AI",
+  "description": "English multi-task CNN trained on OntoNotes. Assigns context-specific token vectors, POS tags, dependency parse and named entities.",
+  "email": "[email protected]",
+  "lang": "en",
+  "license": "MIT",
+  "name": "core_web_sm",
+  "parent_package": "spacy-nightly",
+  "pipeline": [
+    "tagger",
+    "parser",
+    "ner"
+  ],
+  "sources": [
+    "OntoNotes 5"
+  ],
+  "spacy_version": ">=2.1.0a4",
+  "speed": {
+    "cpu": 7435.3852845254,
+    "gpu": null,
+    "nwords": 291344
+  },
+  "url": "https://explosion.ai",
+  "version": "2.1.0a6",
+  "size": "10 MB",
+  "checksum": "927785b2aabb43d888437295a11b071798570dbd8c67cf80c611bc1c6927898c"
+}