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:
- e9d1dc0489269b966b09f9664075a7fb183721f844537a1c733474bbdaa63d66
- Size of remote file:
- 2.1 kB
- SHA256:
- a0eae1fb01475a2434e6ce45356e764e9d567efedff16ac7ee77c63b9a6e4e2c
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