Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use mldev/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mldev/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mldev/bert-finetuned-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mldev/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("mldev/bert-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from mldev/bert-finetuned-ner: direct link, hf CLI and curl.
- Browser
- Download file 3.06 kB
-
https://huggingface.co/mldev/bert-finetuned-ner/resolve/main/training_args.bin
- Command line
-
hf download hf://mldev/bert-finetuned-ner/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/mldev/bert-finetuned-ner/resolve/main/training_args.bin
3.06 kB
- Xet hash:
- 0eb48a93c08ca88e2267b999cfa0351b2a1f0a023bbe9dd64c206f811daff2e3
- Size of remote file:
- 3.06 kB
- SHA256:
- cfb8e4e406f13c5dd2a59e540680ff93b46821b6aaa2da1fdf98ef8537afc8a4
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