Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use shre-db/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shre-db/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="shre-db/bert-finetuned-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("shre-db/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("shre-db/bert-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from shre-db/bert-finetuned-ner: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/shre-db/bert-finetuned-ner/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://shre-db/bert-finetuned-ner/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/shre-db/bert-finetuned-ner/resolve/main/pytorch_model.bin
431 MB
- Xet hash:
- 2a6a111e4397fe305aed027a7c6587f121288d4f5a0dfcd281b0321425acc1bf
- Size of remote file:
- 431 MB
- SHA256:
- eaae4e4dbb19af6d2198e7ebb333599127da9b2b959a92fa5e51be82c3c02799
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