Instructions to use KoichiYasuoka/roberta-base-chinese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KoichiYasuoka/roberta-base-chinese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="KoichiYasuoka/roberta-base-chinese")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("KoichiYasuoka/roberta-base-chinese") model = AutoModelForMaskedLM.from_pretrained("KoichiYasuoka/roberta-base-chinese") - Notebooks
- Google Colab
- Kaggle
roberta-base-chinese
Model Description
This is a RoBERTa model pre-trained on Chinese Wikipedia texts (both simplified and traditional). NVIDIA A100-SXM4-40GB took 48 hours 56 minutes for training. You can fine-tune roberta-base-chinese for downstream tasks, such as POS-tagging, dependency-parsing, and so on.
How to Use
from transformers import AutoTokenizer,AutoModelForMaskedLM
tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/roberta-base-chinese")
model=AutoModelForMaskedLM.from_pretrained("KoichiYasuoka/roberta-base-chinese")
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