adrianeboyd
commited on
Commit
•
940f852
1
Parent(s):
26f494b
Update spaCy pipeline
Browse files- README.md +28 -28
- accuracy.json +193 -193
- attribute_ruler/patterns +0 -0
- config.cfg +5 -4
- lemmatizer/model +1 -1
- meta.json +196 -196
- morphologizer/model +1 -1
- nb_core_news_md-any-py3-none-any.whl +2 -2
- ner/model +2 -2
- parser/model +1 -1
- senter/model +1 -1
- tok2vec/model +2 -2
- tokenizer +1 -1
- vocab/strings.json +2 -2
README.md
CHANGED
@@ -14,62 +14,62 @@ model-index:
|
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14 |
metrics:
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- name: NER Precision
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type: precision
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-
value: 0.
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- name: NER Recall
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type: recall
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-
value: 0.
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- name: NER F Score
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type: f_score
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-
value: 0.
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- task:
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name: TAG
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type: token-classification
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metrics:
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- name: TAG (XPOS) Accuracy
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type: accuracy
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-
value: 0.
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- task:
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name: POS
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type: token-classification
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metrics:
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- name: POS (UPOS) Accuracy
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type: accuracy
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-
value: 0.
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- task:
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name: MORPH
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type: token-classification
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metrics:
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- name: Morph (UFeats) Accuracy
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type: accuracy
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-
value: 0.
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- task:
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name: LEMMA
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type: token-classification
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metrics:
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- name: Lemma Accuracy
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type: accuracy
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-
value: 0.
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- task:
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name: UNLABELED_DEPENDENCIES
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type: token-classification
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metrics:
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- name: Unlabeled Attachment Score (UAS)
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type: f_score
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-
value: 0.
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- task:
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name: LABELED_DEPENDENCIES
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type: token-classification
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metrics:
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- name: Labeled Attachment Score (LAS)
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type: f_score
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-
value: 0.
|
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- task:
|
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name: SENTS
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type: token-classification
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metrics:
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- name: Sentences F-Score
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type: f_score
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-
value: 0.
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---
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### Details: https://spacy.io/models/nb#nb_core_news_md
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|
@@ -78,8 +78,8 @@ Norwegian (Bokmål) pipeline optimized for CPU. Components: tok2vec, morphologiz
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| Feature | Description |
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| --- | --- |
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| **Name** | `nb_core_news_md` |
|
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-
| **Version** | `3.
|
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-
| **spaCy** | `>=3.
|
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| **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` |
|
84 |
| **Components** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` |
|
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| **Vectors** | 500000 keys, 20000 unique vectors (300 dimensions) |
|
@@ -105,22 +105,22 @@ Norwegian (Bokmål) pipeline optimized for CPU. Components: tok2vec, morphologiz
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| Type | Score |
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| --- | --- |
|
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-
| `TOKEN_ACC` | 99.
|
109 |
| `TOKEN_P` | 99.71 |
|
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| `TOKEN_R` | 99.53 |
|
111 |
| `TOKEN_F` | 99.62 |
|
112 |
-
| `POS_ACC` | 97.
|
113 |
-
| `MORPH_ACC` | 95.
|
114 |
-
| `MORPH_MICRO_P` | 97.
|
115 |
-
| `MORPH_MICRO_R` | 96.
|
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-
| `MORPH_MICRO_F` | 97.
|
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-
| `SENTS_P` |
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-
| `SENTS_R` |
|
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-
| `SENTS_F` |
|
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-
| `DEP_UAS` | 89.
|
121 |
-
| `DEP_LAS` | 86.
|
122 |
-
| `LEMMA_ACC` | 97.
|
123 |
-
| `TAG_ACC` | 97.
|
124 |
-
| `ENTS_P` |
|
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-
| `ENTS_R` |
|
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-
| `ENTS_F` |
|
|
|
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metrics:
|
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- name: NER Precision
|
16 |
type: precision
|
17 |
+
value: 0.811827957
|
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- name: NER Recall
|
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type: recall
|
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+
value: 0.8050947867
|
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- name: NER F Score
|
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type: f_score
|
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+
value: 0.8084473528
|
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- task:
|
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name: TAG
|
26 |
type: token-classification
|
27 |
metrics:
|
28 |
- name: TAG (XPOS) Accuracy
|
29 |
type: accuracy
|
30 |
+
value: 0.9728910684
|
31 |
- task:
|
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name: POS
|
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type: token-classification
|
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metrics:
|
35 |
- name: POS (UPOS) Accuracy
|
36 |
type: accuracy
|
37 |
+
value: 0.9728910684
|
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- task:
|
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name: MORPH
|
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type: token-classification
|
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metrics:
|
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- name: Morph (UFeats) Accuracy
|
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type: accuracy
|
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+
value: 0.9586576479
|
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- task:
|
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name: LEMMA
|
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type: token-classification
|
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metrics:
|
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- name: Lemma Accuracy
|
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type: accuracy
|
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+
value: 0.970965787
|
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- task:
|
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name: UNLABELED_DEPENDENCIES
|
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type: token-classification
|
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metrics:
|
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- name: Unlabeled Attachment Score (UAS)
|
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type: f_score
|
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+
value: 0.8936788796
|
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- task:
|
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name: LABELED_DEPENDENCIES
|
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type: token-classification
|
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metrics:
|
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- name: Labeled Attachment Score (LAS)
|
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type: f_score
|
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+
value: 0.8623767174
|
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- task:
|
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name: SENTS
|
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type: token-classification
|
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metrics:
|
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- name: Sentences F-Score
|
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type: f_score
|
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+
value: 0.9485952133
|
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---
|
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### Details: https://spacy.io/models/nb#nb_core_news_md
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|
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| Feature | Description |
|
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| --- | --- |
|
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| **Name** | `nb_core_news_md` |
|
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+
| **Version** | `3.5.0` |
|
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+
| **spaCy** | `>=3.5.0,<3.6.0` |
|
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| **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` |
|
84 |
| **Components** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` |
|
85 |
| **Vectors** | 500000 keys, 20000 unique vectors (300 dimensions) |
|
|
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|
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| Type | Score |
|
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| --- | --- |
|
108 |
+
| `TOKEN_ACC` | 99.81 |
|
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| `TOKEN_P` | 99.71 |
|
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| `TOKEN_R` | 99.53 |
|
111 |
| `TOKEN_F` | 99.62 |
|
112 |
+
| `POS_ACC` | 97.29 |
|
113 |
+
| `MORPH_ACC` | 95.87 |
|
114 |
+
| `MORPH_MICRO_P` | 97.59 |
|
115 |
+
| `MORPH_MICRO_R` | 96.65 |
|
116 |
+
| `MORPH_MICRO_F` | 97.12 |
|
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+
| `SENTS_P` | 95.12 |
|
118 |
+
| `SENTS_R` | 94.60 |
|
119 |
+
| `SENTS_F` | 94.86 |
|
120 |
+
| `DEP_UAS` | 89.37 |
|
121 |
+
| `DEP_LAS` | 86.24 |
|
122 |
+
| `LEMMA_ACC` | 97.10 |
|
123 |
+
| `TAG_ACC` | 97.29 |
|
124 |
+
| `ENTS_P` | 81.18 |
|
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+
| `ENTS_R` | 80.51 |
|
126 |
+
| `ENTS_F` | 80.84 |
|
accuracy.json
CHANGED
@@ -1,63 +1,63 @@
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@@ -65,191 +65,186 @@
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@@ -261,25 +256,30 @@
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@@ -287,52 +287,52 @@
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attribute_ruler/patterns
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|
config.cfg
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@@ -81,8 +81,8 @@ nO = null
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|
81 |
[components.ner.model.tok2vec.embed]
|
82 |
@architectures = "spacy.MultiHashEmbed.v2"
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83 |
width = 96
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84 |
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attrs = ["NORM","PREFIX","SUFFIX","SHAPE"
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rows = [5000,1000,2500,2500
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86 |
include_static_vectors = true
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87 |
|
88 |
[components.ner.model.tok2vec.encode]
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@@ -150,8 +150,8 @@ factory = "tok2vec"
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|
150 |
[components.tok2vec.model.embed]
|
151 |
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|
152 |
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153 |
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attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY"]
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154 |
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rows = [5000,1000,2500,2500,50]
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156 |
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[components.tok2vec.model.encode]
|
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193 |
frozen_components = []
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195 |
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196 |
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197 |
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|
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|
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81 |
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87 |
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88 |
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|
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lemmatizer/model
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vocab/strings.json
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