Instructions to use Azma-AI/bert-uncased-keyword-extractor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Azma-AI/bert-uncased-keyword-extractor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Azma-AI/bert-uncased-keyword-extractor")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Azma-AI/bert-uncased-keyword-extractor") model = AutoModelForTokenClassification.from_pretrained("Azma-AI/bert-uncased-keyword-extractor") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:0a8cf7c54e279845bae0ee8feb469c0adf6ea57f9f4e52aee7ac509d673562d9
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size 435603348
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