Text Classification
Transformers
Safetensors
Chinese
bert
content-moderation
sensitive-word-detection
text-embeddings-inference
Instructions to use crackrammer/ShieldBERT-Base-Chinese-Sensitive with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use crackrammer/ShieldBERT-Base-Chinese-Sensitive with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="crackrammer/ShieldBERT-Base-Chinese-Sensitive")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("crackrammer/ShieldBERT-Base-Chinese-Sensitive") model = AutoModelForSequenceClassification.from_pretrained("crackrammer/ShieldBERT-Base-Chinese-Sensitive") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("crackrammer/ShieldBERT-Base-Chinese-Sensitive")
model = AutoModelForSequenceClassification.from_pretrained("crackrammer/ShieldBERT-Base-Chinese-Sensitive")Quick Links
这是一个基于 bert-base-chinese 微调的敏感词检测模型,专门用于识别中文文本中的敏感、成人及违规内容。
协议声明
本模型权重及相关代码采用 Apache License 2.0 协议开源。
- Downloads last month
- 3
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="crackrammer/ShieldBERT-Base-Chinese-Sensitive")