Instructions to use fhswf/bert_de_ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fhswf/bert_de_ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="fhswf/bert_de_ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("fhswf/bert_de_ner") model = AutoModelForTokenClassification.from_pretrained("fhswf/bert_de_ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from fhswf/bert_de_ner: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/fhswf/bert_de_ner/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://fhswf/bert_de_ner/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/fhswf/bert_de_ner/resolve/main/pytorch_model.bin
440 MB
- Xet hash:
- 8c4a448911eeaba32d505b9674cfa5e33fe936e24718aa959e8f9843729a2905
- Size of remote file:
- 440 MB
- SHA256:
- a474845d03c6af2b2a8b616dfc7f3bd997821a906adf5ea13b511ad10c22e23f
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