initial release

README.md

@@ -1,3 +1,40 @@
----
-license: cc-by-sa-4.0
----
+---
+language:
+- "be"
+tags:
+- "belarusian"
+- "token-classification"
+- "pos"
+- "dependency-parsing"
+datasets:
+- "universal_dependencies"
+license: "cc-by-sa-4.0"
+pipeline_tag: "token-classification"
+---
+
+# roberta-small-belarusian-upos
+
+## Model Description
+
+This is a RoBERTa model pre-trained with [UD_Belarusian](https://universaldependencies.org/be/) for POS-tagging and dependency-parsing, derived from [roberta-small-belarusian](https://huggingface.co/KoichiYasuoka/roberta-small-belarusian). Every word is tagged by [UPOS](https://universaldependencies.org/u/pos/) (Universal Part-Of-Speech).
+
+## How to Use
+
+```py
+import torch
+from transformers import AutoTokenizer,AutoModelForTokenClassification
+tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/roberta-small-belarusian-upos")
+model=AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/roberta-small-belarusian-upos")
+```
+
+or
+
+```
+import esupar
+nlp=esupar.load("KoichiYasuoka/roberta-small-belarusian-upos")
+```
+
+## See Also
+
+[esupar](https://github.com/KoichiYasuoka/esupar): Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa models
+

config.json

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+{
+  "architectures": [
+    "RobertaForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 2,
+  "classifier_dropout": null,
+  "eos_token_id": 3,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 256,
+  "id2label": {
+    "0": "ADJ",
+    "1": "ADP",
+    "2": "ADV",
+    "3": "AUX",
+    "4": "B-ADJ",
+    "5": "B-ADP",
+    "6": "B-ADV",
+    "7": "B-AUX",
+    "8": "B-CCONJ",
+    "9": "B-DET",
+    "10": "B-INTJ",
+    "11": "B-NOUN",
+    "12": "B-NUM",
+    "13": "B-PART",
+    "14": "B-PRON",
+    "15": "B-PROPN",
+    "16": "B-PUNCT",
+    "17": "B-SCONJ",
+    "18": "B-SYM",
+    "19": "B-VERB",
+    "20": "B-X",
+    "21": "CCONJ",
+    "22": "DET",
+    "23": "I-ADJ",
+    "24": "I-ADP",
+    "25": "I-ADV",
+    "26": "I-AUX",
+    "27": "I-CCONJ",
+    "28": "I-DET",
+    "29": "I-INTJ",
+    "30": "I-NOUN",
+    "31": "I-NUM",
+    "32": "I-PART",
+    "33": "I-PRON",
+    "34": "I-PROPN",
+    "35": "I-PUNCT",
+    "36": "I-SCONJ",
+    "37": "I-SYM",
+    "38": "I-VERB",
+    "39": "I-X",
+    "40": "INTJ",
+    "41": "NOUN",
+    "42": "NUM",
+    "43": "PART",
+    "44": "PRON",
+    "45": "PROPN",
+    "46": "PUNCT",
+    "47": "SCONJ",
+    "48": "SYM",
+    "49": "VERB",
+    "50": "X"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 768,
+  "label2id": {
+    "ADJ": 0,
+    "ADP": 1,
+    "ADV": 2,
+    "AUX": 3,
+    "B-ADJ": 4,
+    "B-ADP": 5,
+    "B-ADV": 6,
+    "B-AUX": 7,
+    "B-CCONJ": 8,
+    "B-DET": 9,
+    "B-INTJ": 10,
+    "B-NOUN": 11,
+    "B-NUM": 12,
+    "B-PART": 13,
+    "B-PRON": 14,
+    "B-PROPN": 15,
+    "B-PUNCT": 16,
+    "B-SCONJ": 17,
+    "B-SYM": 18,
+    "B-VERB": 19,
+    "B-X": 20,
+    "CCONJ": 21,
+    "DET": 22,
+    "I-ADJ": 23,
+    "I-ADP": 24,
+    "I-ADV": 25,
+    "I-AUX": 26,
+    "I-CCONJ": 27,
+    "I-DET": 28,
+    "I-INTJ": 29,
+    "I-NOUN": 30,
+    "I-NUM": 31,
+    "I-PART": 32,
+    "I-PRON": 33,
+    "I-PROPN": 34,
+    "I-PUNCT": 35,
+    "I-SCONJ": 36,
+    "I-SYM": 37,
+    "I-VERB": 38,
+    "I-X": 39,
+    "INTJ": 40,
+    "NOUN": 41,
+    "NUM": 42,
+    "PART": 43,
+    "PRON": 44,
+    "PROPN": 45,
+    "PUNCT": 46,
+    "SCONJ": 47,
+    "SYM": 48,
+    "VERB": 49,
+    "X": 50
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 128,
+  "model_type": "roberta",
+  "num_attention_heads": 4,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "tokenizer_class": "BertTokenizerFast",
+  "torch_dtype": "float32",
+  "transformers_version": "4.17.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30000
+}

pytorch_model.bin

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+size 62598033

special_tokens_map.json

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+{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}

supar.model

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+oid sha256:c70647136e8bce1ad7f73a3a1624f1046a1834a6a85bbef5c464e73eb1337f56
+size 117684157

tokenizer_config.json

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+{"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, "do_lowercase": false, "never_split": ["[CLS]", "[PAD]", "[SEP]", "[UNK]", "[MASK]"], "do_basic_tokenize": true, "model_max_length": 128, "tokenizer_class": "BertTokenizerFast"}