initial release

README.md

@@ -1,3 +1,42 @@
 ---
-license: cc-by-sa-4.0
+language:
+- "cop"
+tags:
+- "coptic"
+- "token-classification"
+- "pos"
+- "dependency-parsing"
+datasets:
+- "universal_dependencies"
+license: "cc-by-sa-4.0"
+pipeline_tag: "token-classification"
+widget:
+- text: "ⲙⲟⲟϣⲉϩⲱⲥϣⲏⲣⲉⲙⲡⲟⲩⲟⲉⲓⲛ"
 ---
+
+# roberta-small-coptic-upos
+
+## Model Description
+
+This is a RoBERTa model pre-trained with [UD_Coptic](https://universaldependencies.org/cop/) for POS-tagging and dependency-parsing, derived from [roberta-small-coptic](https://huggingface.co/KoichiYasuoka/roberta-small-coptic). 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-coptic-upos")
+model=AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/roberta-small-coptic-upos")
+```
+
+or
+
+```
+import esupar
+nlp=esupar.load("KoichiYasuoka/roberta-small-coptic-upos")
+```
+
+## See Also
+
+[esupar](https://github.com/KoichiYasuoka/esupar): Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa models
+

pytorch_model.bin

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+size 36995441

sentencepiece.model

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special_tokens_map.json

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+{"bos_token": "[CLS]", "eos_token": "[SEP]", "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": {"content": "[MASK]", "single_word": false, "lstrip": true, "rstrip": false, "normalized": true}}

supar.model

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+size 80700325

tokenizer_config.json

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+{"do_lower_case": false, "remove_space": true, "keep_accents": true, "bos_token": "[CLS]", "eos_token": "[SEP]", "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": {"content": "[MASK]", "single_word": false, "lstrip": true, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "model_max_length": 128, "tokenizer_class": "RemBertTokenizerFast"}