Token Classification
Transformers
PyTorch
English
roberta
keyphrase-extraction
Eval Results (legacy)
Instructions to use ml6team/keyphrase-extraction-kbir-kpcrowd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ml6team/keyphrase-extraction-kbir-kpcrowd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ml6team/keyphrase-extraction-kbir-kpcrowd")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ml6team/keyphrase-extraction-kbir-kpcrowd") model = AutoModelForTokenClassification.from_pretrained("ml6team/keyphrase-extraction-kbir-kpcrowd") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 644c3c3c02b414439931b9a549410262f82ab69eeec46a0afa52a1c29b462dec
- Size of remote file:
- 1.42 GB
- SHA256:
- 365c26c2f4da604d8288a9e84678967d8afc658da3fd76a6cb7b62c2e0975d80
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