Add model metas (#22)

Add model metas Co-authored-by: Explosion Bot <[email protected]>
explosion · Oct 8, 2019 · 79eeb72 · 79eeb72
2 parents 7379fc4 + acc64c6
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diff --git a/meta/de_trf_bertbasecased_lg-2.2.0.json b/meta/de_trf_bertbasecased_lg-2.2.0.json
@@ -0,0 +1,37 @@
+{
+  "lang": "de",
+  "lang_factory": "trf",
+  "name": "trf_bertbasecased_lg",
+  "description": "Provides weights and configuration for the pretrained transformer model `bert-base-german-cased`, published by deepset. The package uses HuggingFace's `transformers` implementation of the model. Pretrained transformer models assign detailed contextual word representations, using knowledge drawn from a large corpus of unlabelled text. You can use the contextual word representations as features in a variety of pipeline components that can be trained on your own data.",
+  "notes": "Requires the `spacy-transformers` package to be installed. A CUDA-compatible GPU is advised for reasonable performance.",
+  "author": "deepset (repackaged by Explosion)",
+  "email": "[email protected]",
+  "url": "https://github.com/explosion/spacy-transformers",
+  "license": "MIT",
+  "sources": [
+    {
+      "name": "bert-base-german-cased",
+      "author": "deepset",
+      "url": "https://deepset.ai/german-bert"
+    }
+  ],
+  "version": "2.2.0",
+  "requirements": [
+    "spacy-transformers>=0.5.0"
+  ],
+  "spacy_version": ">=2.2.1",
+  "vectors": {
+    "width": 0,
+    "vectors": 0,
+    "keys": 0,
+    "name": null
+  },
+  "pipeline": [
+    "sentencizer",
+    "trf_wordpiecer",
+    "trf_tok2vec"
+  ],
+  "labels": {},
+  "size": "386 MB",
+  "checksum": "f9f27bfd138f5b55b3177bb2d933d1825a107275f599c11797f9c2f5dea048b4"
+}
diff --git a/meta/en_trf_bertbaseuncased_lg-2.2.0.json b/meta/en_trf_bertbaseuncased_lg-2.2.0.json
@@ -0,0 +1,37 @@
+{
+  "lang": "en",
+  "lang_factory": "trf",
+  "name": "trf_bertbaseuncased_lg",
+  "description": "Provides weights and configuration for the pretrained transformer model `bert-base-uncased`, published by Google Research. The package uses HuggingFace's `transformers` implementation of the model. Pretrained transformer models assign detailed contextual word representations, using knowledge drawn from a large corpus of unlabelled text. You can use the contextual word representations as features in a variety of pipeline components that can be trained on your own data.",
+  "notes": "Requires the `spacy-transformers` package to be installed. A CUDA-compatible GPU is advised for reasonable performance.",
+  "author": "Google Research (repackaged by Explosion)",
+  "email": "[email protected]",
+  "url": "https://github.com/explosion/spacy-transformers",
+  "license": "MIT",
+  "sources": [
+    {
+      "name": "bert-base-uncased",
+      "author": "Google Research",
+      "url": "https://github.com/google-research/bert"
+    }
+  ],
+  "version": "2.2.0",
+  "requirements": [
+    "spacy-transformers>=0.5.0"
+  ],
+  "spacy_version": ">=2.2.1",
+  "vectors": {
+    "width": 0,
+    "vectors": 0,
+    "keys": 0,
+    "name": null
+  },
+  "pipeline": [
+    "sentencizer",
+    "trf_wordpiecer",
+    "trf_tok2vec"
+  ],
+  "labels": {},
+  "size": "387 MB",
+  "checksum": "c2fa0f48ff5bf176a69ee0439a8d9b9f068a8805be8de60d38b1cac071d149c4"
+}
diff --git a/meta/en_trf_distilbertbaseuncased_lg-2.2.0.json b/meta/en_trf_distilbertbaseuncased_lg-2.2.0.json
@@ -0,0 +1,37 @@
+{
+  "lang": "en",
+  "lang_factory": "trf",
+  "name": "trf_distilbertbaseuncased_lg",
+  "description": "Provides weights and configuration for the pretrained transformer model `distilbert-base-uncased`, published by Hugging Face. The package uses HuggingFace's `transformers` implementation of the model. Pretrained transformer models assign detailed contextual word representations, using knowledge drawn from a large corpus of unlabelled text. You can use the contextual word representations as features in a variety of pipeline components that can be trained on your own data.",
+  "notes": "Requires the `spacy-transformers` package to be installed. A CUDA-compatible GPU is advised for reasonable performance.",
+  "author": "Hugging Face (repackaged by Explosion)",
+  "email": "[email protected]",
+  "url": "https://github.com/explosion/spacy-transformers",
+  "license": "MIT",
+  "sources": [
+    {
+      "name": "distilbert-base-uncased",
+      "author": "Hugging Face",
+      "url": "https://medium.com/huggingface/distilbert-8cf3380435b5"
+    }
+  ],
+  "version": "2.2.0",
+  "requirements": [
+    "spacy-transformers>=0.5.0"
+  ],
+  "spacy_version": ">=2.2.1",
+  "vectors": {
+    "width": 0,
+    "vectors": 0,
+    "keys": 0,
+    "name": null
+  },
+  "pipeline": [
+    "sentencizer",
+    "trf_wordpiecer",
+    "trf_tok2vec"
+  ],
+  "labels": {},
+  "size": "233 MB",
+  "checksum": "be221dadce03599e57da5c7341abe323ad2fb1a5990a342288745f25d20dc854"
+}
diff --git a/meta/en_trf_robertabase_lg-2.2.0.json b/meta/en_trf_robertabase_lg-2.2.0.json
@@ -0,0 +1,37 @@
+{
+  "lang": "en",
+  "lang_factory": "trf",
+  "name": "trf_robertabase_lg",
+  "description": "Provides weights and configuration for the pretrained transformer model `roberta-base`, published by Facebook. The package uses HuggingFace's `transformers` implementation of the model. Pretrained transformer models assign detailed contextual word representations, using knowledge drawn from a large corpus of unlabelled text. You can use the contextual word representations as features in a variety of pipeline components that can be trained on your own data.",
+  "notes": "Requires the `spacy-transformers` package to be installed. A CUDA-compatible GPU is advised for reasonable performance.",
+  "author": "Facebook (repackaged by Explosion)",
+  "email": "[email protected]",
+  "url": "https://github.com/explosion/spacy-transformers",
+  "license": "MIT",
+  "sources": [
+    {
+      "name": "roberta-base",
+      "author": "Facebook",
+      "url": "https://github.com/pytorch/fairseq/tree/master/examples/roberta"
+    }
+  ],
+  "version": "2.2.0",
+  "requirements": [
+    "spacy-transformers>=0.5.0"
+  ],
+  "spacy_version": ">=2.2.1",
+  "vectors": {
+    "width": 0,
+    "vectors": 0,
+    "keys": 0,
+    "name": null
+  },
+  "pipeline": [
+    "sentencizer",
+    "trf_wordpiecer",
+    "trf_tok2vec"
+  ],
+  "labels": {},
+  "size": "278 MB",
+  "checksum": "cf32b4f5dbbd3ac4e2584f1cec77a91ceabc3b452005380b652bfc890de80680"
+}
diff --git a/meta/en_trf_xlnetbasecased_lg-2.2.0.json b/meta/en_trf_xlnetbasecased_lg-2.2.0.json
@@ -0,0 +1,37 @@
+{
+  "lang": "en",
+  "lang_factory": "trf",
+  "name": "trf_xlnetbasecased_lg",
+  "description": "Provides weights and configuration for the pretrained transformer model `xlnet-base-cased`, published by CMU and Google Brain. The package uses HuggingFace's `transformers` implementation of the model. Pretrained transformer models assign detailed contextual word representations, using knowledge drawn from a large corpus of unlabelled text. You can use the contextual word representations as features in a variety of pipeline components that can be trained on your own data.",
+  "notes": "Requires the `spacy-transformers` package to be installed. A CUDA-compatible GPU is advised for reasonable performance.",
+  "author": "CMU & Google Brain (repackaged by Explosion)",
+  "email": "[email protected]",
+  "url": "https://github.com/explosion/spacy-transformers",
+  "license": "MIT",
+  "sources": [
+    {
+      "name": "xlnet-base-cased",
+      "author": "CMU & Google Brain",
+      "url": "https://github.com/zihangdai/xlnet/"
+    }
+  ],
+  "version": "2.2.0",
+  "requirements": [
+    "spacy-transformers>=0.5.0"
+  ],
+  "spacy_version": ">=2.2.1",
+  "vectors": {
+    "width": 0,
+    "vectors": 0,
+    "keys": 0,
+    "name": null
+  },
+  "pipeline": [
+    "sentencizer",
+    "trf_wordpiecer",
+    "trf_tok2vec"
+  ],
+  "labels": {},
+  "size": "413 MB",
+  "checksum": "e769e3180783457f26136638a5b664a068b7a711b0c8dd6c01187cc7d0ee9ccf"
+}