Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use awilli/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use awilli/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="awilli/bert-finetuned-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("awilli/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("awilli/bert-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from awilli/bert-finetuned-ner: direct link, hf CLI and curl.
- Browser
- Download file 3.18 kB
-
https://huggingface.co/awilli/bert-finetuned-ner/resolve/main/training_args.bin
- Command line
-
hf download hf://awilli/bert-finetuned-ner/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/awilli/bert-finetuned-ner/resolve/main/training_args.bin
3.18 kB
- Xet hash:
- 8f09ecedb49bc3909c2de250326d6bd1391f011796dac520443b2753c504d9b9
- Size of remote file:
- 3.18 kB
- SHA256:
- e602c2c6c370238893323f03854feb6af6fb93cce36f6f1a27eccf05030519a5
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