initial release

README.md

@@ -1,3 +1,48 @@
----
-license: apache-2.0
----
+---
+language:
+- "th"
+tags:
+- "thai"
+- "token-classification"
+- "pos"
+- "wikipedia"
+- "dependency-parsing"
+datasets:
+- "universal_dependencies"
+license: "apache-2.0"
+pipeline_tag: "token-classification"
+widget:
+- text: "หลายหัวดีกว่าหัวเดียว"
+---
+
+# roberta-base-thai-char-upos
+
+## Model Description
+
+This is a RoBERTa model pre-trained on Thai Wikipedia texts for POS-tagging and dependency-parsing, derived from [roberta-base-thai-char](https://huggingface.co/KoichiYasuoka/roberta-base-thai-char). 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-base-thai-char-upos")
+model=AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/roberta-base-thai-char-upos")
+s="หลายหัวดีกว่าหัวเดียว"
+t=tokenizer.tokenize(s)
+p=[model.config.id2label[q] for q in torch.argmax(model(tokenizer.encode(s,return_tensors="pt"))["logits"],dim=2)[0].tolist()[1:-1]]
+print(list(zip(t,p)))
+```
+
+or
+
+```
+import esupar
+nlp=esupar.load("KoichiYasuoka/roberta-base-thai-char-upos")
+print(nlp("หลายหัวดีกว่าหัวเดียว"))
+```
+
+## 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": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "ADP",
+    "1": "ADV",
+    "2": "B-ADJ",
+    "3": "B-ADP",
+    "4": "B-ADV",
+    "5": "B-AUX",
+    "6": "B-CCONJ",
+    "7": "B-DET",
+    "8": "B-INTJ",
+    "9": "B-NOUN",
+    "10": "B-NUM",
+    "11": "B-PART",
+    "12": "B-PRON",
+    "13": "B-PROPN",
+    "14": "B-PUNCT",
+    "15": "B-SCONJ",
+    "16": "B-VERB",
+    "17": "B-X",
+    "18": "CCONJ",
+    "19": "DET",
+    "20": "I-ADJ",
+    "21": "I-ADP",
+    "22": "I-ADV",
+    "23": "I-AUX",
+    "24": "I-CCONJ",
+    "25": "I-DET",
+    "26": "I-INTJ",
+    "27": "I-NOUN",
+    "28": "I-NUM",
+    "29": "I-PART",
+    "30": "I-PRON",
+    "31": "I-PROPN",
+    "32": "I-PUNCT",
+    "33": "I-SCONJ",
+    "34": "I-VERB",
+    "35": "I-X",
+    "36": "NOUN",
+    "37": "NUM",
+    "38": "PART",
+    "39": "PRON",
+    "40": "PROPN",
+    "41": "PUNCT",
+    "42": "SYM",
+    "43": "VERB",
+    "44": "X"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
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+    "B-ADJ": 2,
+    "B-ADP": 3,
+    "B-ADV": 4,
+    "B-AUX": 5,
+    "B-CCONJ": 6,
+    "B-DET": 7,
+    "B-INTJ": 8,
+    "B-NOUN": 9,
+    "B-NUM": 10,
+    "B-PART": 11,
+    "B-PRON": 12,
+    "B-PROPN": 13,
+    "B-PUNCT": 14,
+    "B-SCONJ": 15,
+    "B-VERB": 16,
+    "B-X": 17,
+    "CCONJ": 18,
+    "DET": 19,
+    "I-ADJ": 20,
+    "I-ADP": 21,
+    "I-ADV": 22,
+    "I-AUX": 23,
+    "I-CCONJ": 24,
+    "I-DET": 25,
+    "I-INTJ": 26,
+    "I-NOUN": 27,
+    "I-NUM": 28,
+    "I-PART": 29,
+    "I-PRON": 30,
+    "I-PROPN": 31,
+    "I-PUNCT": 32,
+    "I-SCONJ": 33,
+    "I-VERB": 34,
+    "I-X": 35,
+    "NOUN": 36,
+    "NUM": 37,
+    "PART": 38,
+    "PRON": 39,
+    "PROPN": 40,
+    "PUNCT": 41,
+    "SYM": 42,
+    "VERB": 43,
+    "X": 44
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "tokenizer_class": "BertTokenizerFast",
+  "torch_dtype": "float32",
+  "transformers_version": "4.14.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 2727
+}

pytorch_model.bin

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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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tokenizer.json

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