Instructions to use ckiplab/albert-tiny-chinese-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ckiplab/albert-tiny-chinese-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ckiplab/albert-tiny-chinese-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ckiplab/albert-tiny-chinese-ner") model = AutoModelForTokenClassification.from_pretrained("ckiplab/albert-tiny-chinese-ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bd1e2dae44e18b2f883d5e409cc25a63e1aaea329b44ad8c52daaff4b4c5f250
- Size of remote file:
- 16 MB
- SHA256:
- 03f6e38f92ada4b59b88ae9122a50a0c98b85f07722ff1234048928e55ed10d3
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