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")# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from dmis-lab/phrase-reranker-multi: direct link, hf CLI and curl.
- Browser
- Download file 1.36 MB
-
https://huggingface.co/dmis-lab/phrase-reranker-multi/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://dmis-lab/phrase-reranker-multi@refs/pr/1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/dmis-lab/phrase-reranker-multi/resolve/refs%2Fpr%2F1/tokenizer.json
1.36 MB
File too large to display, you can check the raw version instead.