Token Classification
Transformers
PyTorch
English
roberta
keyphrase-extraction
Eval Results (legacy)
Instructions to use ml6team/keyphrase-extraction-kbir-inspec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ml6team/keyphrase-extraction-kbir-inspec with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ml6team/keyphrase-extraction-kbir-inspec")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ml6team/keyphrase-extraction-kbir-inspec") model = AutoModelForTokenClassification.from_pretrained("ml6team/keyphrase-extraction-kbir-inspec", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 0b80417
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README.md
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### Training parameters
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### Preprocessing
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The documents in the dataset are already preprocessed into list of words with the corresponding labels. The only thing that must be done is tokenization and the realignment of the labels so that they correspond with the right subword tokens.
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### Training parameters
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| Parameter | Value |
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| Learning Rate | 1e-4 |
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| Epochs | 50 |
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| Early Stopping Patience | 3 |
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### Preprocessing
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The documents in the dataset are already preprocessed into list of words with the corresponding labels. The only thing that must be done is tokenization and the realignment of the labels so that they correspond with the right subword tokens.
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