Token Classification
Transformers
PyTorch
English
roberta
keyphrase-extraction
Eval Results (legacy)
Instructions to use ml6team/keyphrase-extraction-kbir-semeval2017 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ml6team/keyphrase-extraction-kbir-semeval2017 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ml6team/keyphrase-extraction-kbir-semeval2017")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ml6team/keyphrase-extraction-kbir-semeval2017") model = AutoModelForTokenClassification.from_pretrained("ml6team/keyphrase-extraction-kbir-semeval2017", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1b4409814750aca3caea4211222edce45654ca7474fd1d8f3af30f6092c0b434
- Size of remote file:
- 3.12 kB
- SHA256:
- acfbe5d9b9acbbe59f5955fcd403ef2957a5406d4042431a93ebe335775e8e3d
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