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
Download tokenizer.json from ml6team/keyphrase-extraction-kbir-semeval2017: direct link, hf CLI and curl.
- Browser
- Download file 2.11 MB
-
https://huggingface.co/ml6team/keyphrase-extraction-kbir-semeval2017/resolve/main/tokenizer.json
- Command line
-
hf download hf://ml6team/keyphrase-extraction-kbir-semeval2017/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ml6team/keyphrase-extraction-kbir-semeval2017/resolve/main/tokenizer.json
2.11 MB
File too large to display, you can check the raw version instead.