Instructions to use praneethvasarla/ner-general-17-classes-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use praneethvasarla/ner-general-17-classes-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="praneethvasarla/ner-general-17-classes-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("praneethvasarla/ner-general-17-classes-bert") model = AutoModelForTokenClassification.from_pretrained("praneethvasarla/ner-general-17-classes-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from praneethvasarla/ner-general-17-classes-bert: direct link, hf CLI and curl.
- Browser
- Download file 4.6 kB
-
https://huggingface.co/praneethvasarla/ner-general-17-classes-bert/resolve/main/training_args.bin
- Command line
-
hf download hf://praneethvasarla/ner-general-17-classes-bert/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/praneethvasarla/ner-general-17-classes-bert/resolve/main/training_args.bin
4.6 kB
- Xet hash:
- 67770e6eb0b0b544a077995032703bb3d7f4ada172ec53f6ce5964942d8d5ec3
- Size of remote file:
- 4.6 kB
- SHA256:
- 031229fabaed558b0999219dc57c437e020439b7698c81510b692509380a63da
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