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 266 MB
-
https://huggingface.co/Kriyans/Bert-NER/resolve/refs%2Fpr%2F2/pytorch_model.bin
- Command line
-
hf download hf://Kriyans/Bert-NER@refs/pr/2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Kriyans/Bert-NER/resolve/refs%2Fpr%2F2/pytorch_model.bin
266 MB
- Xet hash:
- 78ad9e86ae328404f35e01eb422ef49b2c1bae5f7bffc1004fa926a2e0c62409
- Size of remote file:
- 266 MB
- SHA256:
- b242fe3fe4f720ee177664df6e54a96e60a0cdcf2637e963a8cffd9b5230c866
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