Token Classification
Transformers
PyTorch
Safetensors
English
French
German
stacked_bert
v1.0.0
custom_code
Instructions to use impresso-project/ner-stacked-bert-multilingual-v1.1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use impresso-project/ner-stacked-bert-multilingual-v1.1.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="impresso-project/ner-stacked-bert-multilingual-v1.1.0", trust_remote_code=True)# Load model directly from transformers import AutoModelForTokenClassification model = AutoModelForTokenClassification.from_pretrained("impresso-project/ner-stacked-bert-multilingual-v1.1.0", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 100e0932631c778ba4e38bc1bb999c246057a144133718809fca7015fcc2444b
- Size of remote file:
- 169 MB
- SHA256:
- d85dc101a70451930bedc505f6ba1b231f42dc8b84795c5515f43e5d715be0a2
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