Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use shamweel/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shamweel/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="shamweel/bert-finetuned-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("shamweel/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("shamweel/bert-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from shamweel/bert-finetuned-ner: direct link, hf CLI and curl.
- Browser
- Download file 3.31 kB
-
https://huggingface.co/shamweel/bert-finetuned-ner/resolve/d7c53737adccbff38c68818061cafd99710e9c39/training_args.bin
- Command line
-
hf download hf://shamweel/bert-finetuned-ner@d7c53737adccbff38c68818061cafd99710e9c39/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/shamweel/bert-finetuned-ner/resolve/d7c53737adccbff38c68818061cafd99710e9c39/training_args.bin
3.31 kB
- Xet hash:
- b0b1be6f082eaca20200f621012574061b14a9e1d48d53c29ae23a4009425cfe
- Size of remote file:
- 3.31 kB
- SHA256:
- da24442bb310f7125a1d4c545a9f8ce5da059918c5488960b29c278fc01b4e03
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