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
File size: 408 Bytes
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license: apache-2.0
language:
- zh
library_name: transformers
pipeline_tag: text-classification
tags:
- bert
- content-moderation
- sensitive-word-detection
---
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](LICENSE) 协议开源。
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