Token Classification
Transformers
PyTorch
Chinese
named-entity-recognition
ner
ernie
crf
chinese-nlp
person-name-extraction
financial-documents
Instructions to use warfbro/Human-Name-extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use warfbro/Human-Name-extraction with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="warfbro/Human-Name-extraction")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("warfbro/Human-Name-extraction", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download llm from warfbro/Human-Name-extraction: direct link, hf CLI and curl.
- Browser
- Download file 215 Bytes
-
https://huggingface.co/warfbro/Human-Name-extraction/resolve/main/llm
- Command line
-
hf download hf://warfbro/Human-Name-extraction/llm
-
curl -L -o llm https://huggingface.co/warfbro/Human-Name-extraction/resolve/main/llm
215 Bytes
| # LLM 配置 — OpenAI 兼容 API 格式 | |
| # 填入你的 API 信息,支持 DeepSeek / Qwen / OpenAI 等服务商 | |
| api_key=sk-your-key-here | |
| api_url=https://api.deepseek.com/chat/completions | |
| model=deepseek-chat | |