Token Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use SamSaver/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SamSaver/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="SamSaver/bert-finetuned-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("SamSaver/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("SamSaver/bert-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from SamSaver/bert-finetuned-ner: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/SamSaver/bert-finetuned-ner/resolve/main/training_args.bin
- Command line
-
hf download hf://SamSaver/bert-finetuned-ner/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/SamSaver/bert-finetuned-ner/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- d9ceae5cf199f9b112325063d01b7a68d59b198c637ba3d6d418d9f2f2c0a16d
- Size of remote file:
- 4.98 kB
- SHA256:
- 164c7d4b95443dabced545c01f1005e0b048bd950cf9cfca8f3740ccefe4ae89
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