Update spaCy pipeline

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Files changed (15) hide show

README.md +28 -28
accuracy.json +167 -167
config.cfg +57 -28
lemmatizer/cfg +343 -354
lemmatizer/model +2 -2
lemmatizer/trees +0 -0
meta.json +174 -172
morphologizer/model +2 -2
ner/model +0 -0
parser/model +0 -0
sl_core_news_trf-any-py3-none-any.whl +2 -2
tagger/model +2 -2
transformer/cfg +1 -1
transformer/model +2 -2
vocab/strings.json +0 -0

README.md CHANGED Viewed

@@ -14,72 +14,72 @@ model-index:
     metrics:
     - name: NER Precision
       type: precision
-      value: 0.8841463415
     - name: NER Recall
       type: recall
-      value: 0.917721519
     - name: NER F Score
       type: f_score
-      value: 0.900621118
   - task:
       name: TAG
       type: token-classification
     metrics:
     - name: TAG (XPOS) Accuracy
       type: accuracy
-      value: 0.9770274602
   - task:
       name: POS
       type: token-classification
     metrics:
     - name: POS (UPOS) Accuracy
       type: accuracy
-      value: 0.9899348221
   - task:
       name: MORPH
       type: token-classification
     metrics:
     - name: Morph (UFeats) Accuracy
       type: accuracy
-      value: 0.9788652634
   - task:
       name: LEMMA
       type: token-classification
     metrics:
     - name: Lemma Accuracy
       type: accuracy
-      value: 0.9679666631
   - task:
       name: UNLABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Unlabeled Attachment Score (UAS)
       type: f_score
-      value: 0.93363503
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Labeled Attachment Score (LAS)
       type: f_score
-      value: 0.9170251386
   - task:
       name: SENTS
       type: token-classification
     metrics:
     - name: Sentences F-Score
       type: f_score
-      value: 0.9373219373
 ---
 ### Details: https://spacy.io/models/sl#sl_core_news_trf
-Slovenian transformer pipeline (EMBEDDIA/sloberta). Components: transformer, tagger, morphologizer, parser, lemmatizer (trainable_lemmatizer), ner.
 | Feature | Description |
 | --- | --- |
 | **Name** | `sl_core_news_trf` |
-| **Version** | `3.6.1` |
-| **spaCy** | `>=3.6.0,<3.7.0` |
 | **Default Pipeline** | `transformer`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` |
 | **Components** | `transformer`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` |
 | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
@@ -110,18 +110,18 @@ Slovenian transformer pipeline (EMBEDDIA/sloberta). Components: transformer, tag
 | `TOKEN_P` | 99.81 |
 | `TOKEN_R` | 99.57 |
 | `TOKEN_F` | 99.69 |
-| `TAG_ACC` | 97.70 |
-| `POS_ACC` | 98.99 |
-| `MORPH_ACC` | 97.89 |
-| `MORPH_MICRO_P` | 99.01 |
-| `MORPH_MICRO_R` | 98.89 |
-| `MORPH_MICRO_F` | 98.95 |
-| `SENTS_P` | 93.20 |
-| `SENTS_R` | 94.27 |
-| `SENTS_F` | 93.73 |
-| `DEP_UAS` | 93.36 |
-| `DEP_LAS` | 91.70 |
-| `LEMMA_ACC` | 96.80 |
-| `ENTS_P` | 88.41 |
-| `ENTS_R` | 91.77 |
-| `ENTS_F` | 90.06 |

     metrics:
     - name: NER Precision
       type: precision
+      value: 0.9316770186
     - name: NER Recall
       type: recall
+      value: 0.9493670886
     - name: NER F Score
       type: f_score
+      value: 0.9404388715
   - task:
       name: TAG
       type: token-classification
     metrics:
     - name: TAG (XPOS) Accuracy
       type: accuracy
+      value: 0.9802329309
   - task:
       name: POS
       type: token-classification
     metrics:
     - name: POS (UPOS) Accuracy
       type: accuracy
+      value: 0.9908323539
   - task:
       name: MORPH
       type: token-classification
     metrics:
     - name: Morph (UFeats) Accuracy
       type: accuracy
+      value: 0.981857036
   - task:
       name: LEMMA
       type: token-classification
     metrics:
     - name: Lemma Accuracy
       type: accuracy
+      value: 0.9694198098
   - task:
       name: UNLABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Unlabeled Attachment Score (UAS)
       type: f_score
+      value: 0.9361807921
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Labeled Attachment Score (LAS)
       type: f_score
+      value: 0.9223081322
   - task:
       name: SENTS
       type: token-classification
     metrics:
     - name: Sentences F-Score
       type: f_score
+      value: 0.9325789722
 ---
 ### Details: https://spacy.io/models/sl#sl_core_news_trf
+Slovenian transformer pipeline (Transformer(name='EMBEDDIA/sloberta', piece_encoder='camembert-sentencepiece', stride=128, type='camembert', width=768, window=168, vocab_size=32005)). Components: transformer, tagger, morphologizer, parser, lemmatizer (trainable_lemmatizer), ner.
 | Feature | Description |
 | --- | --- |
 | **Name** | `sl_core_news_trf` |
+| **Version** | `3.7.2` |
+| **spaCy** | `>=3.7.0,<3.8.0` |
 | **Default Pipeline** | `transformer`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` |
 | **Components** | `transformer`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` |
 | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
 | `TOKEN_P` | 99.81 |
 | `TOKEN_R` | 99.57 |
 | `TOKEN_F` | 99.69 |
+| `TAG_ACC` | 98.02 |
+| `POS_ACC` | 99.08 |
+| `MORPH_ACC` | 98.19 |
+| `MORPH_MICRO_P` | 99.15 |
+| `MORPH_MICRO_R` | 99.04 |
+| `MORPH_MICRO_F` | 99.09 |
+| `SENTS_P` | 92.09 |
+| `SENTS_R` | 94.46 |
+| `SENTS_F` | 93.26 |
+| `DEP_UAS` | 93.62 |
+| `DEP_LAS` | 92.23 |
+| `LEMMA_ACC` | 96.94 |
+| `ENTS_P` | 93.17 |
+| `ENTS_R` | 94.94 |
+| `ENTS_F` | 94.04 |

accuracy.json CHANGED Viewed

@@ -3,57 +3,57 @@
   "token_p": 0.9980762654,
   "token_r": 0.9956925964,
   "token_f": 0.996883006,
-  "tag_acc": 0.9770274602,
-  "pos_acc": 0.9899348221,
-  "morph_acc": 0.9788652634,
-  "morph_micro_p": 0.9900582551,
-  "morph_micro_r": 0.9888854047,
-  "morph_micro_f": 0.9894714824,
   "morph_per_feat": {
     "Case": {
-      "p": 0.9839550079,
-      "r": 0.9840363937,
-      "f": 0.9839956991
     },
     "Gender": {
-      "p": 0.9841089671,
-      "r": 0.9844814534,
-      "f": 0.984295175
     },
     "Number": {
-      "p": 0.9930539296,
-      "r": 0.9932864949,
-      "f": 0.9931701986
     },
     "Aspect": {
-      "p": 0.9868204283,
-      "r": 0.9933665008,
-      "f": 0.9900826446
     },
     "Mood": {
-      "p": 0.9951520494,
-      "r": 0.9947136564,
-      "f": 0.9949328046
     },
     "Person": {
-      "p": 0.9972166998,
-      "r": 0.9964243147,
-      "f": 0.9968203498
     },
     "Tense": {
-      "p": 0.9980582524,
-      "r": 0.9951597289,
-      "f": 0.9966068832
     },
     "VerbForm": {
-      "p": 0.997615894,
-      "r": 0.9949801849,
-      "f": 0.9962962963
     },
     "PronType": {
-      "p": 0.9929214929,
       "r": 0.995483871,
-      "f": 0.9942010309
     },
     "Variant": {
       "p": 0.9981412639,
@@ -62,18 +62,18 @@
     },
     "NumForm": {
       "p": 1.0,
-      "r": 0.9617834395,
-      "f": 0.9805194805
     },
     "NumType": {
       "p": 1.0,
-      "r": 0.9653179191,
-      "f": 0.9823529412
     },
     "Degree": {
-      "p": 0.9925989183,
-      "r": 0.9923164485,
-      "f": 0.9924576633
     },
     "Polarity": {
       "p": 1.0,
@@ -81,14 +81,14 @@
       "f": 0.9992902768
     },
     "Number[psor]": {
-      "p": 0.9375,
-      "r": 0.9375,
-      "f": 0.9375
     },
     "Poss": {
-      "p": 1.0,
-      "r": 0.995,
-      "f": 0.9974937343
     },
     "Reflex": {
       "p": 0.9975,
@@ -101,9 +101,9 @@
       "f": 0.9896551724
     },
     "Animacy": {
-      "p": 0.9634831461,
-      "r": 0.9346049046,
-      "f": 0.948824343
     },
     "Abbr": {
       "p": 1.0,
@@ -111,186 +111,186 @@
       "f": 1.0
     },
     "Foreign": {
-      "p": 0.8947368421,
-      "r": 0.4473684211,
-      "f": 0.5964912281
     },
     "Gender[psor]": {
-      "p": 0.9090909091,
       "r": 0.9090909091,
-      "f": 0.9090909091
     }
   },
-  "sents_p": 0.9320113314,
-  "sents_r": 0.9426934097,
-  "sents_f": 0.9373219373,
-  "dep_uas": 0.93363503,
-  "dep_las": 0.9170251386,
   "dep_las_per_type": {
     "nsubj": {
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-      "r": 0.8850515464,
-      "f": 0.8924116424
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     "root": {
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-      "f": 0.9441527446
     },
     "obj": {
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-      "f": 0.9353905497
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-      "f": 0.9281767956
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-      "r": 0.625,
-      "f": 0.6081081081
     },
     "flat": {
-      "p": 0.6086956522,
-      "r": 0.7368421053,
-      "f": 0.6666666667
     },
     "orphan": {
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-      "r": 0.4583333333,
-      "f": 0.5365853659
     },
     "advcl": {
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-      "f": 0.7391304348
     },
     "fixed": {
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       "r": 0.8658536585,
-      "f": 0.816091954
     },
     "flat:foreign": {
-      "p": 0.625,
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-    },
-    "dep": {
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     },
     "discourse": {
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       "r": 0.6428571429,
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     "cc:preconj": {
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@@ -298,25 +298,25 @@
       "f": 0.8421052632
     }
   },
-  "lemma_acc": 0.9679666631,
-  "ents_p": 0.8841463415,
-  "ents_r": 0.917721519,
-  "ents_f": 0.900621118,
   "ents_per_type": {
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     "MISC": {
       "p": 0.75,
@@ -329,5 +329,5 @@
       "f": 0.6666666667
     }
   },
-  "speed": 1211.6699495749
 }

   "token_p": 0.9980762654,
   "token_r": 0.9956925964,
   "token_f": 0.996883006,
+  "tag_acc": 0.9802329309,
+  "pos_acc": 0.9908323539,
+  "morph_acc": 0.981857036,
+  "morph_micro_p": 0.9914889164,
+  "morph_micro_r": 0.9903661893,
+  "morph_micro_f": 0.9909272349,
   "morph_per_feat": {
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     "Gender": {
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     "Person": {
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+  "sents_f": 0.9325789722,
+  "dep_uas": 0.9361807921,
+  "dep_las": 0.9223081322,
   "dep_las_per_type": {
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     "aux": {
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     "det": {
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     "advmod": {
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     },
     "expl": {
+      "p": 0.961414791,
+      "r": 0.9583333333,
+      "f": 0.9598715891
     },
     "xcomp": {
+      "p": 0.9440993789,
+      "r": 0.95,
+      "f": 0.9470404984
     },
     "ccomp": {
+      "p": 0.9184782609,
+      "r": 0.9184782609,
+      "f": 0.9184782609
+    },
+    "dep": {
+      "p": 0.0465116279,
+      "r": 0.3333333333,
+      "f": 0.0816326531
     },
     "appos": {
+      "p": 0.6258503401,
+      "r": 0.6388888889,
+      "f": 0.6323024055
     },
     "flat": {
+      "p": 0.7647058824,
+      "r": 0.6842105263,
+      "f": 0.7222222222
     },
     "orphan": {
+      "p": 0.6478873239,
+      "r": 0.4791666667,
+      "f": 0.5508982036
     },
     "advcl": {
+      "p": 0.7486910995,
+      "r": 0.680952381,
+      "f": 0.7132169576
     },
     "fixed": {
+      "p": 0.9393939394,
+      "r": 0.9393939394,
+      "f": 0.9393939394
     },
     "list": {
+      "p": 0.7553191489,
       "r": 0.8658536585,
+      "f": 0.8068181818
     },
     "flat:foreign": {
+      "p": 0.6666666667,
+      "r": 0.5,
+      "f": 0.5714285714
     },
     "discourse": {
+      "p": 0.9,
       "r": 0.6428571429,
+      "f": 0.75
     },
     "vocative": {
+      "p": 0.5,
       "r": 0.2,
+      "f": 0.2857142857
     },
     "cc:preconj": {
       "p": 1.0,
       "f": 0.8421052632
     }
   },
+  "lemma_acc": 0.9694198098,
+  "ents_p": 0.9316770186,
+  "ents_r": 0.9493670886,
+  "ents_f": 0.9404388715,
   "ents_per_type": {
     "ORG": {
+      "p": 0.9189189189,
+      "r": 0.85,
+      "f": 0.8831168831
     },
     "PER": {
       "p": 1.0,
+      "r": 1.0,
+      "f": 1.0
     },
     "LOC": {
+      "p": 0.8965517241,
       "r": 0.962962963,
+      "f": 0.9285714286
     },
     "MISC": {
       "p": 0.75,
       "f": 0.6666666667
     }
   },
+  "speed": 1008.1462815944
 }

config.cfg CHANGED Viewed

@@ -17,6 +17,7 @@ after_creation = null
 after_pipeline_creation = null
 batch_size = 64
 tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
 [components]
@@ -39,10 +40,11 @@ nO = null
 normalize = false
 [components.lemmatizer.model.tok2vec]
-@architectures = "spacy-transformers.TransformerListener.v1"
-grad_factor = 1.0
 upstream = "transformer"
 pooling = {"@layers":"reduce_mean.v1"}
 [components.morphologizer]
 factory = "morphologizer"
@@ -57,10 +59,11 @@ nO = null
 normalize = false
 [components.morphologizer.model.tok2vec]
-@architectures = "spacy-transformers.TransformerListener.v1"
-grad_factor = 1.0
 upstream = "transformer"
 pooling = {"@layers":"reduce_mean.v1"}
 [components.ner]
 factory = "ner"
@@ -79,10 +82,11 @@ use_upper = false
 nO = null
 [components.ner.model.tok2vec]
-@architectures = "spacy-transformers.TransformerListener.v1"
-grad_factor = 1.0
 upstream = "transformer"
 pooling = {"@layers":"reduce_mean.v1"}
 [components.parser]
 factory = "parser"
@@ -102,10 +106,11 @@ use_upper = false
 nO = null
 [components.parser.model.tok2vec]
-@architectures = "spacy-transformers.TransformerListener.v1"
-grad_factor = 1.0
 upstream = "transformer"
 pooling = {"@layers":"reduce_mean.v1"}
 [components.tagger]
 factory = "tagger"
@@ -120,32 +125,44 @@ nO = null
 normalize = false
 [components.tagger.model.tok2vec]
-@architectures = "spacy-transformers.TransformerListener.v1"
-grad_factor = 1.0
 upstream = "transformer"
 pooling = {"@layers":"reduce_mean.v1"}
 [components.transformer]
-factory = "transformer"
-max_batch_items = 4096
-set_extra_annotations = {"@annotation_setters":"spacy-transformers.null_annotation_setter.v1"}
 [components.transformer.model]
-name = "EMBEDDIA/sloberta"
-@architectures = "spacy-transformers.TransformerModel.v3"
 mixed_precision = false
-[components.transformer.model.get_spans]
-@span_getters = "spacy-transformers.strided_spans.v1"
-window = 128
-stride = 96
 [components.transformer.model.grad_scaler_config]
-[components.transformer.model.tokenizer_config]
-use_fast = true
-[components.transformer.model.transformer_config]
 [corpora]
@@ -182,11 +199,11 @@ annotating_components = []
 before_update = null
 [training.batcher]
-@batchers = "spacy.batch_by_padded.v1"
-discard_oversize = true
-get_length = null
 size = 2000
-buffer = 256
 [training.logger]
 @loggers = "spacy.ConsoleLogger.v1"
@@ -272,6 +289,18 @@ require = false
 path = "corpus/labels/tagger.json"
 require = false
 [initialize.lookups]
 @misc = "spacy.LookupsDataLoader.v1"
 lang = ${nlp.lang}

 after_pipeline_creation = null
 batch_size = 64
 tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
+vectors = {"@vectors":"spacy.Vectors.v1"}
 [components]
 normalize = false
 [components.lemmatizer.model.tok2vec]
+@architectures = "spacy-curated-transformers.LastTransformerLayerListener.v1"
+width = ${components.transformer.model.hidden_width}
 upstream = "transformer"
 pooling = {"@layers":"reduce_mean.v1"}
+grad_factor = 1.0
 [components.morphologizer]
 factory = "morphologizer"
 normalize = false
 [components.morphologizer.model.tok2vec]
+@architectures = "spacy-curated-transformers.LastTransformerLayerListener.v1"
+width = ${components.transformer.model.hidden_width}
 upstream = "transformer"
 pooling = {"@layers":"reduce_mean.v1"}
+grad_factor = 1.0
 [components.ner]
 factory = "ner"
 nO = null
 [components.ner.model.tok2vec]
+@architectures = "spacy-curated-transformers.LastTransformerLayerListener.v1"
+width = ${components.transformer.model.hidden_width}
 upstream = "transformer"
 pooling = {"@layers":"reduce_mean.v1"}
+grad_factor = 1.0
 [components.parser]
 factory = "parser"
 nO = null
 [components.parser.model.tok2vec]
+@architectures = "spacy-curated-transformers.LastTransformerLayerListener.v1"
+width = ${components.transformer.model.hidden_width}
 upstream = "transformer"
 pooling = {"@layers":"reduce_mean.v1"}
+grad_factor = 1.0
 [components.tagger]
 factory = "tagger"
 normalize = false
 [components.tagger.model.tok2vec]
+@architectures = "spacy-curated-transformers.LastTransformerLayerListener.v1"
+width = ${components.transformer.model.hidden_width}
 upstream = "transformer"
 pooling = {"@layers":"reduce_mean.v1"}
+grad_factor = 1.0
 [components.transformer]
+factory = "curated_transformer"
+all_layer_outputs = false
+frozen = false
 [components.transformer.model]
+@architectures = "spacy-curated-transformers.CamembertTransformer.v1"
+vocab_size = 32005
+hidden_width = 768
+piece_encoder = {"@architectures":"spacy-curated-transformers.CamembertSentencepieceEncoder.v1"}
+attention_probs_dropout_prob = 0.1
+hidden_act = "gelu"
+hidden_dropout_prob = 0.1
+intermediate_width = 3072
+layer_norm_eps = 0.00001
+max_position_embeddings = 514
+model_max_length = 512
+num_attention_heads = 12
+num_hidden_layers = 12
+padding_idx = 1
+type_vocab_size = 1
 mixed_precision = false
+torchscript = false
+wrapped_listener = null
 [components.transformer.model.grad_scaler_config]
+[components.transformer.model.with_spans]
+@architectures = "spacy-curated-transformers.WithStridedSpans.v1"
+stride = 128
+window = 168
+batch_size = 384
 [corpora]
 before_update = null
 [training.batcher]
+@batchers = "spacy.batch_by_words.v1"
+discard_oversize = false
 size = 2000
+tolerance = 0.2
+get_length = null
 [training.logger]
 @loggers = "spacy.ConsoleLogger.v1"
 path = "corpus/labels/tagger.json"
 require = false
+[initialize.components.transformer]
+[initialize.components.transformer.encoder_loader]
+@model_loaders = "spacy-curated-transformers.HFTransformerEncoderLoader.v1"
+name = "EMBEDDIA/sloberta"
+revision = "main"
+[initialize.components.transformer.piecer_loader]
+@model_loaders = "spacy-curated-transformers.HFPieceEncoderLoader.v1"
+name = "EMBEDDIA/sloberta"
+revision = "main"
 [initialize.lookups]
 @misc = "spacy.LookupsDataLoader.v1"
 lang = ${nlp.lang}

lemmatizer/cfg CHANGED Viewed

@@ -102,31 +102,31 @@
     202,
     204,
     206,
-    208,
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@@ -135,418 +135,422 @@
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     279,
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@@ -557,42 +561,38 @@
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@@ -618,7 +618,6 @@
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@@ -647,313 +646,312 @@
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@@ -1006,7 +1004,7 @@
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@@ -1025,98 +1023,89 @@
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 }

 {
   "lang":"sl",
   "name":"core_news_trf",
+  "version":"3.7.2",
+  "description":"Slovenian transformer pipeline (Transformer(name='EMBEDDIA/sloberta', piece_encoder='camembert-sentencepiece', stride=128, type='camembert', width=768, window=168, vocab_size=32005)). Components: transformer, tagger, morphologizer, parser, lemmatizer (trainable_lemmatizer), ner.",
   "author":"Explosion",
   "email":"[email protected]",
   "url":"https://explosion.ai",
   "license":"CC BY-SA 4.0",
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 }

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