Instructions to use universalner/uner_chn_gsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use universalner/uner_chn_gsd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="universalner/uner_chn_gsd")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("universalner/uner_chn_gsd") model = AutoModelForTokenClassification.from_pretrained("universalner/uner_chn_gsd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ae9c322c85dd5b95113c6f552be57a8d1b0a3e51a755732c714d3d46c7af5071
- Size of remote file:
- 2.24 GB
- SHA256:
- c3fbc6609ead7769989e602050371c25c8b01706a8dd9b9e365555624e8491f4
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