Instructions to use dmis-lab/phrase-reranker-multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dmis-lab/phrase-reranker-multi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dmis-lab/phrase-reranker-multi")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dmis-lab/phrase-reranker-multi") model = AutoModelForSequenceClassification.from_pretrained("dmis-lab/phrase-reranker-multi") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ced939e8cc7deff4c7b3ae17f3d75ff7c2b62c0ed776abe99f15b45a05543f3
- Size of remote file:
- 3.12 kB
- SHA256:
- 3a701be665bcf585bc46b7e4960134e6f692e6bdb0b0a61f7588808e3010b305
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