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)# pip install -U transformers accelerate # 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, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from HavelockAI/bert-token-classifier: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/HavelockAI/bert-token-classifier/resolve/e7adbd7c417eb94b338abd577affc6fd5bfcdbac/tokenizer.json
- Command line
-
hf download hf://HavelockAI/bert-token-classifier@e7adbd7c417eb94b338abd577affc6fd5bfcdbac/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/HavelockAI/bert-token-classifier/resolve/e7adbd7c417eb94b338abd577affc6fd5bfcdbac/tokenizer.json
712 kB
File too large to display, you can check the raw version instead.