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
Download training_args.bin from impresso-project/ner-stacked-bert-multilingual-light: direct link, hf CLI and curl.
- Browser
- Download file 2.1 kB
-
https://huggingface.co/impresso-project/ner-stacked-bert-multilingual-light/resolve/main/training_args.bin
- Command line
-
hf download hf://impresso-project/ner-stacked-bert-multilingual-light/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/impresso-project/ner-stacked-bert-multilingual-light/resolve/main/training_args.bin
2.1 kB
- Xet hash:
- 501f5f8001c2dbb5585bb0b3e6881953c3212cd00a8a4c234667b653b457d60c
- Size of remote file:
- 2.1 kB
- SHA256:
- cc92dca5d693d80c40bfa708d0ee9551d1f85b832c57710b3edfc72dc86707e1
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