Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use Ce/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ce/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Ce/bert-finetuned-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Ce/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("Ce/bert-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Ce/bert-finetuned-ner: direct link, hf CLI and curl.
- Browser
- Download file 3.18 kB
-
https://huggingface.co/Ce/bert-finetuned-ner/resolve/main/training_args.bin
- Command line
-
hf download hf://Ce/bert-finetuned-ner/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Ce/bert-finetuned-ner/resolve/main/training_args.bin
3.18 kB
- Xet hash:
- 3c749f8f71860175b5108137f8fe884b75f5145cdef09bd46be7667a69188b80
- Size of remote file:
- 3.18 kB
- SHA256:
- b10083889df016d61286bf2c7500d4d67d777f149b32f8b4a3c1bddf34db8f24
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