Instructions to use wl-tookitaki/bge_reranker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wl-tookitaki/bge_reranker with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wl-tookitaki/bge_reranker")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wl-tookitaki/bge_reranker") model = AutoModelForSequenceClassification.from_pretrained("wl-tookitaki/bge_reranker", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fbda5c09afc337d55ed31158cc27054cb7ba8f640b48dafe18b6e4b72c0c517a
- Size of remote file:
- 5.24 kB
- SHA256:
- cf5dc7d256bf53c6379abc1146c103d88e9ef1b9c4b2b430345d8a0067eb75d8
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