Token Classification
Transformers
Safetensors
English
modernbert
fill-mask
orality
linguistics
multi-label
custom_code
Instructions to use HavelockAI/bert-token-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HavelockAI/bert-token-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="HavelockAI/bert-token-classifier", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("HavelockAI/bert-token-classifier", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("HavelockAI/bert-token-classifier", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d0aacf4e6c95b124b797f7aebb2172e45f91619e577261aeb2ef452144477555
- Size of remote file:
- 597 MB
- SHA256:
- 5048514ce9b2156eb090a211c30847979362fe5372cb94865373a00b5970726d
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