KoichiYasuoka commited on
Commit
c5aae34
1 Parent(s): e3b42c3

initial release

Browse files
README.md CHANGED
@@ -1,3 +1,41 @@
1
- ---
2
- license: cc-by-sa-4.0
3
- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ language:
3
+ - "uk"
4
+ tags:
5
+ - "ukrainian"
6
+ - "token-classification"
7
+ - "pos"
8
+ - "ubertext"
9
+ - "dependency-parsing"
10
+ datasets:
11
+ - "universal_dependencies"
12
+ license: "cc-by-sa-4.0"
13
+ pipeline_tag: "token-classification"
14
+ ---
15
+
16
+ # roberta-base-ukrainian-upos
17
+
18
+ ## Model Description
19
+
20
+ This is a RoBERTa model pre-trained on Thai Wikipedia texts for POS-tagging and dependency-parsing, derived from [roberta-base-ukrainian](https://huggingface.co/KoichiYasuoka/roberta-base-ukrainian). Every word is tagged by [UPOS](https://universaldependencies.org/u/pos/) (Universal Part-Of-Speech).
21
+
22
+ ## How to Use
23
+
24
+ ```py
25
+ import torch
26
+ from transformers import AutoTokenizer,AutoModelForTokenClassification
27
+ tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/roberta-base-ukrainian-upos")
28
+ model=AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/roberta-base-ukrainian-upos")
29
+ ```
30
+
31
+ or
32
+
33
+ ```
34
+ import esupar
35
+ nlp=esupar.load("KoichiYasuoka/roberta-base-ukrainian-upos")
36
+ ```
37
+
38
+ ## See Also
39
+
40
+ [esupar](https://github.com/KoichiYasuoka/esupar): Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa models
41
+
config.json ADDED
@@ -0,0 +1,223 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "architectures": [
3
+ "RobertaForTokenClassification"
4
+ ],
5
+ "attention_probs_dropout_prob": 0.1,
6
+ "bos_token_id": 0,
7
+ "classifier_dropout": null,
8
+ "eos_token_id": 2,
9
+ "hidden_act": "gelu",
10
+ "hidden_dropout_prob": 0.1,
11
+ "hidden_size": 768,
12
+ "id2label": {
13
+ "0": "ADJ",
14
+ "1": "ADP",
15
+ "2": "ADV",
16
+ "3": "AUX",
17
+ "4": "B-ADJ",
18
+ "5": "B-ADP",
19
+ "6": "B-ADV",
20
+ "7": "B-AUX",
21
+ "8": "B-CCONJ",
22
+ "9": "B-DET",
23
+ "10": "B-INTJ",
24
+ "11": "B-NOUN",
25
+ "12": "B-NOUN+NUM",
26
+ "13": "B-NUM",
27
+ "14": "B-NUM+NOUN",
28
+ "15": "B-PART",
29
+ "16": "B-PRON",
30
+ "17": "B-PROPN",
31
+ "18": "B-PUNCT",
32
+ "19": "B-SCONJ",
33
+ "20": "B-SYM",
34
+ "21": "B-VERB",
35
+ "22": "B-VERB+ADV",
36
+ "23": "B-VERB+PRON",
37
+ "24": "B-X",
38
+ "25": "CCONJ",
39
+ "26": "DET",
40
+ "27": "I-ADJ",
41
+ "28": "I-ADP",
42
+ "29": "I-ADV",
43
+ "30": "I-AUX",
44
+ "31": "I-CCONJ",
45
+ "32": "I-DET",
46
+ "33": "I-INTJ",
47
+ "34": "I-NOUN",
48
+ "35": "I-NOUN+NUM",
49
+ "36": "I-NUM",
50
+ "37": "I-NUM+NOUN",
51
+ "38": "I-PART",
52
+ "39": "I-PRON",
53
+ "40": "I-PROPN",
54
+ "41": "I-PUNCT",
55
+ "42": "I-SCONJ",
56
+ "43": "I-SYM",
57
+ "44": "I-VERB",
58
+ "45": "I-VERB+ADV",
59
+ "46": "I-VERB+PRON",
60
+ "47": "I-X",
61
+ "48": "INTJ",
62
+ "49": "NOUN",
63
+ "50": "NOUN+NUM",
64
+ "51": "NUM",
65
+ "52": "NUM+NOUN",
66
+ "53": "PART",
67
+ "54": "PRON",
68
+ "55": "PROPN",
69
+ "56": "PUNCT",
70
+ "57": "SCONJ",
71
+ "58": "SYM",
72
+ "59": "VERB",
73
+ "60": "VERB+ADV",
74
+ "61": "VERB+PRON",
75
+ "62": "X"
76
+ },
77
+ "initializer_range": 0.02,
78
+ "intermediate_size": 3072,
79
+ "label2id": {
80
+ "ADJ": 0,
81
+ "ADP": 1,
82
+ "ADV": 2,
83
+ "AUX": 3,
84
+ "B-ADJ": 4,
85
+ "B-ADP": 5,
86
+ "B-ADV": 6,
87
+ "B-AUX": 7,
88
+ "B-CCONJ": 8,
89
+ "B-DET": 9,
90
+ "B-INTJ": 10,
91
+ "B-NOUN": 11,
92
+ "B-NOUN+NUM": 12,
93
+ "B-NUM": 13,
94
+ "B-NUM+NOUN": 14,
95
+ "B-PART": 15,
96
+ "B-PRON": 16,
97
+ "B-PROPN": 17,
98
+ "B-PUNCT": 18,
99
+ "B-SCONJ": 19,
100
+ "B-SYM": 20,
101
+ "B-VERB": 21,
102
+ "B-VERB+ADV": 22,
103
+ "B-VERB+PRON": 23,
104
+ "B-X": 24,
105
+ "CCONJ": 25,
106
+ "DET": 26,
107
+ "I-ADJ": 27,
108
+ "I-ADP": 28,
109
+ "I-ADV": 29,
110
+ "I-AUX": 30,
111
+ "I-CCONJ": 31,
112
+ "I-DET": 32,
113
+ "I-INTJ": 33,
114
+ "I-NOUN": 34,
115
+ "I-NOUN+NUM": 35,
116
+ "I-NUM": 36,
117
+ "I-NUM+NOUN": 37,
118
+ "I-PART": 38,
119
+ "I-PRON": 39,
120
+ "I-PROPN": 40,
121
+ "I-PUNCT": 41,
122
+ "I-SCONJ": 42,
123
+ "I-SYM": 43,
124
+ "I-VERB": 44,
125
+ "I-VERB+ADV": 45,
126
+ "I-VERB+PRON": 46,
127
+ "I-X": 47,
128
+ "INTJ": 48,
129
+ "NOUN": 49,
130
+ "NOUN+NUM": 50,
131
+ "NUM": 51,
132
+ "NUM+NOUN": 52,
133
+ "PART": 53,
134
+ "PRON": 54,
135
+ "PROPN": 55,
136
+ "PUNCT": 56,
137
+ "SCONJ": 57,
138
+ "SYM": 58,
139
+ "VERB": 59,
140
+ "VERB+ADV": 60,
141
+ "VERB+PRON": 61,
142
+ "X": 62
143
+ },
144
+ "layer_norm_eps": 1e-12,
145
+ "max_position_embeddings": 512,
146
+ "model_type": "roberta",
147
+ "num_attention_heads": 12,
148
+ "num_hidden_layers": 12,
149
+ "pad_token_id": 1,
150
+ "position_embedding_type": "absolute",
151
+ "task_specific_params": {
152
+ "upos_multiword": {
153
+ "NUM+NOUN": {
154
+ "\u043f\u0456\u0432'\u044f\u0440\u0434\u0430": [
155
+ "\u043f\u0456\u0432",
156
+ "\u044f\u0440\u0434\u0430"
157
+ ],
158
+ "\u043f\u0456\u0432\u0440\u043e\u043a\u0443": [
159
+ "\u043f\u0456\u0432",
160
+ "\u0440\u043e\u043a\u0443"
161
+ ],
162
+ "\u043f\u0456\u0432\u2019\u044f\u0433\u043d\u044f\u0442\u0438": [
163
+ "\u043f\u0456\u0432",
164
+ "\u044f\u0433\u043d\u044f\u0442\u0438"
165
+ ],
166
+ "\u043f\u0456\u0432\u2019\u044f\u0437\u0438\u043a\u0430": [
167
+ "\u043f\u0456\u0432",
168
+ "\u044f\u0437\u0438\u043a\u0430"
169
+ ],
170
+ "\u043f\u0456\u0432\u2019\u044f\u0449\u0438\u043a\u0430": [
171
+ "\u043f\u0456\u0432",
172
+ "\u044f\u0449\u0438\u043a\u0430"
173
+ ]
174
+ },
175
+ "VERB+ADV": {
176
+ "\u043d\u0456\u0434\u0435": [
177
+ "\u043d\u0435\u043c\u0430\u0454",
178
+ "\u0434\u0435"
179
+ ],
180
+ "\u043d\u0456\u0437\u0432\u0456\u0434\u043a\u0438": [
181
+ "\u043d\u0435\u043c\u0430\u0454",
182
+ "\u0437\u0432\u0456\u0434\u043a\u0438"
183
+ ],
184
+ "\u043d\u0456\u043a\u043e\u043b\u0438": [
185
+ "\u043d\u0435\u043c\u0430\u0454",
186
+ "\u043a\u043e\u043b\u0438"
187
+ ],
188
+ "\u043d\u0456\u043a\u0443\u0434\u0438": [
189
+ "\u043d\u0435\u043c\u0430\u0454",
190
+ "\u043a\u0443\u0434\u0438"
191
+ ],
192
+ "\u043d\u0456\u044f\u043a": [
193
+ "\u043d\u0435\u043c\u0430\u0454",
194
+ "\u044f\u043a"
195
+ ]
196
+ },
197
+ "VERB+PRON": {
198
+ "\u043d\u0456\u043a\u0438\u043c": [
199
+ "\u043d\u0435\u043c\u0430\u0454",
200
+ "\u043a\u0438\u043c"
201
+ ],
202
+ "\u043d\u0456\u043a\u043e\u0433\u043e": [
203
+ "\u043d\u0435\u043c\u0430\u0454",
204
+ "\u043a\u043e\u0433\u043e"
205
+ ],
206
+ "\u043d\u0456\u043a\u043e\u043c\u0443": [
207
+ "\u043d\u0435\u043c\u0430\u0454",
208
+ "\u043a\u043e\u043c\u0443"
209
+ ],
210
+ "\u043d\u0456\u0447\u0438\u043c": [
211
+ "\u043d\u0435\u043c\u0430\u0454",
212
+ "\u0447\u0438\u043c"
213
+ ]
214
+ }
215
+ }
216
+ },
217
+ "tokenizer_class": "BertTokenizerFast",
218
+ "torch_dtype": "float32",
219
+ "transformers_version": "4.14.1",
220
+ "type_vocab_size": 2,
221
+ "use_cache": true,
222
+ "vocab_size": 30000
223
+ }
pytorch_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:735ce76697fea88bd807ed7cf843d11a691c2fb81c9637a5f42f9f6848ceb7ac
3
+ size 434241393
special_tokens_map.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}
supar.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:16e19fd58bfb82b801655327a1b4ded01417a453e643091ea6baef06bf5ad6b4
3
+ size 487153701
tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
tokenizer_config.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": false, "lowercase": false, "never_split": ["[CLS]", "[PAD]", "[SEP]", "[UNK]", "[MASK]"], "do_basic_tokenize": true, "model_max_length": 512, "tokenizer_class": "BertTokenizerFast"}
vocab.txt ADDED
The diff for this file is too large to render. See raw diff