Instructions to use miugod/mbert_trim_ende_wwm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use miugod/mbert_trim_ende_wwm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="miugod/mbert_trim_ende_wwm")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("miugod/mbert_trim_ende_wwm") model = AutoModelForMaskedLM.from_pretrained("miugod/mbert_trim_ende_wwm") - Notebooks
- Google Colab
- Kaggle
mbert_trim_ende_wwm
该模型基于bert-base-multilingual-cased,使用TextPruner对词表进行裁剪,保留iwslt14德英数据集,用于测试bert-fused的翻译效果。 并且在iwslt14德英数据集上使用全词掩码wwm微调,数据的拼接方式是: de, en, de[sep]en, en[sep]de。
Model Details
lang:德英
vocab_size: 119547 -> 21443
model_size: 682M -> 392M
iwslt14 de_en BLEU: ?
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