Token Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use nicoheiniger/bert-ner-custom with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nicoheiniger/bert-ner-custom with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="nicoheiniger/bert-ner-custom")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("nicoheiniger/bert-ner-custom") model = AutoModelForTokenClassification.from_pretrained("nicoheiniger/bert-ner-custom", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from nicoheiniger/bert-ner-custom: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/nicoheiniger/bert-ner-custom/resolve/main/training_args.bin
- Command line
-
hf download hf://nicoheiniger/bert-ner-custom/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/nicoheiniger/bert-ner-custom/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- 3355e5963bd94919928823f355f6d4975fc245f448f4fdce79fa39fdb2147864
- Size of remote file:
- 5.18 kB
- SHA256:
- b1a677c06525835050a47f2c7ab61dee8ecf315e110dd77bc34a575d5aa1bef9
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