Instructions to use tuhailong/chinese-roberta-wwm-ext with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tuhailong/chinese-roberta-wwm-ext with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="tuhailong/chinese-roberta-wwm-ext")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("tuhailong/chinese-roberta-wwm-ext") model = AutoModelForMaskedLM.from_pretrained("tuhailong/chinese-roberta-wwm-ext") - Notebooks
- Google Colab
- Kaggle
Data
unsupervise train data is E-commerce dialogue, about 20w sentence pairs.
Model
model is chinese-roberta-wwm-ext
Usage
>>> from transformers import AutoTokenizer, AutoModel
>>> model = AutoModel.from_pretrained("tuhailong/chinese-roberta-wwm-ext")
>>> tokenizer = AutoTokenizer.from_pretrained("tuhailong/chinese-roberta-wwm-ext")
>>> sentences_str_list = ["δ»ε€©ε€©ζ°δΈιη","倩ζ°δΈιη"]
>>> inputs = tokenizer(sentences_str_list,return_tensors="pt", padding='max_length', truncation=True, max_length=32)
>>> outputs = model(**inputs)
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