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--- |
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language: |
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- "bo" |
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tags: |
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- "tibetan" |
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- "masked-lm" |
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license: "cc-by-sa-4.0" |
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pipeline_tag: "fill-mask" |
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mask_token: "[MASK]" |
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datasets: |
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- UTibetNLP/tibetan_news_classification |
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--- |
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# roberta-base-tibetan |
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## Model Description |
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This is a RoBERTa model pre-trained on Tibetan texts. NVIDIA A100-SXM4-40GB took 40 hours 44 minutes for training. You can fine-tune `roberta-base-tibetan` for downstream tasks, such as POS-tagging, dependency-parsing, and so on. |
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## How to Use |
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```py |
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from transformers import AutoTokenizer,AutoModelForMaskedLM |
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tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/roberta-base-tibetan") |
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model=AutoModelForMaskedLM.from_pretrained("KoichiYasuoka/roberta-base-tibetan") |
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``` |
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