Instructions to use Sebbones/bert-finetuned-ner-requirements with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sebbones/bert-finetuned-ner-requirements with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Sebbones/bert-finetuned-ner-requirements")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Sebbones/bert-finetuned-ner-requirements") model = AutoModelForTokenClassification.from_pretrained("Sebbones/bert-finetuned-ner-requirements", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Sebbones/bert-finetuned-ner-requirements: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/Sebbones/bert-finetuned-ner-requirements/resolve/main/training_args.bin
- Command line
-
hf download hf://Sebbones/bert-finetuned-ner-requirements/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Sebbones/bert-finetuned-ner-requirements/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- d06faa0f67ef692f6bb6435953a20d578c07130ac41bf5bf2b0a1cb9b89e310c
- Size of remote file:
- 5.37 kB
- SHA256:
- 02a88cd86d1c5fcdbd02bfc9cf62e72f7eb18477679364709ff6adfed693b493
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