Token Classification
Transformers
PyTorch
Safetensors
English
bert
software engineering
ner
named-entity recognition
Instructions to use taidng/wikiser-bert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use taidng/wikiser-bert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="taidng/wikiser-bert-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("taidng/wikiser-bert-base") model = AutoModelForTokenClassification.from_pretrained("taidng/wikiser-bert-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (c6374a75b10aa060781c2e79f62e983428c08bea) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>4f41609
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update paper
00a1620
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initial commit for wikiser-bert-base
da7b78c
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initial commit
d3a3c1e