Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use AJGP/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AJGP/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="AJGP/bert-finetuned-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("AJGP/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("AJGP/bert-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from AJGP/bert-finetuned-ner: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/AJGP/bert-finetuned-ner/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://AJGP/bert-finetuned-ner/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/AJGP/bert-finetuned-ner/resolve/main/pytorch_model.bin
431 MB
- Xet hash:
- b477737779f64ee07f6491e03347e839a310890a6cff31437d787177aab5df8a
- Size of remote file:
- 431 MB
- SHA256:
- f136b366fb2bd2b2e159837cb18b549b225cc5a647f2c2b09ab96891bb361885
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