Token Classification
Transformers
PyTorch
TensorBoard
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use Kriyans/Bert-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kriyans/Bert-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Kriyans/Bert-NER")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Kriyans/Bert-NER") model = AutoModelForTokenClassification.from_pretrained("Kriyans/Bert-NER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Kriyans/Bert-NER: direct link, hf CLI and curl.
- Browser
- Download file 265 MB
-
https://huggingface.co/Kriyans/Bert-NER/resolve/refs%2Fpr%2F4/pytorch_model.bin
- Command line
-
hf download hf://Kriyans/Bert-NER@refs/pr/4/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Kriyans/Bert-NER/resolve/refs%2Fpr%2F4/pytorch_model.bin
265 MB
- Xet hash:
- 5181eacb1a6ffb4e504d11eb3a20bd3ccf3c0518c55b20c6eaba977743ebde36
- Size of remote file:
- 265 MB
- SHA256:
- 8fcc4a59fd190dcad34616f4c4253c56d97ae3b8ef95a7ea8d50ab5d234b95c9
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