Token Classification
Transformers
PyTorch
Safetensors
English
French
German
stacked_bert
v1.0.0
custom_code
Instructions to use impresso-project/ner-stacked-bert-multilingual-light 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-light 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-light", trust_remote_code=True)# Load model directly from transformers import AutoModelForTokenClassification model = AutoModelForTokenClassification.from_pretrained("impresso-project/ner-stacked-bert-multilingual-light", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c93acc9c4c9a4664fb87aefb706c131b37fe8127f1fcf4d068680172c48639cd
- Size of remote file:
- 169 MB
- SHA256:
- 4693904ab70f0ef7c0249db6c23b0b1e3b2760629d8dafa9010f5ec9feb7de39
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