Token Classification
Transformers
TensorFlow
TensorBoard
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use dsfdsf2/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dsfdsf2/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dsfdsf2/bert-finetuned-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("dsfdsf2/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("dsfdsf2/bert-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dsfdsf2/bert-finetuned-ner: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/dsfdsf2/bert-finetuned-ner/resolve/main/training_args.bin
- Command line
-
hf download hf://dsfdsf2/bert-finetuned-ner/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dsfdsf2/bert-finetuned-ner/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- 708dc4606b421115c63c38afd090c37ae16b85fae42016f8a159453d107a5da1
- Size of remote file:
- 4.98 kB
- SHA256:
- 3e68f5679ac6dec0bec98a8ee7a3cae943411c762b58bcd566fda1f8dcf83b0d
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