Instructions to use openbmb/MiniCPM-Reranker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openbmb/MiniCPM-Reranker with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="openbmb/MiniCPM-Reranker", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("openbmb/MiniCPM-Reranker", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update model metadata to set pipeline tag to the new `text-ranking` and tags to `sentence-transformers`
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by tomaarsen HF Staff - opened
README.md
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base_model: openbmb/MiniCPM-2B-sft-bf16
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pipeline_tag: text-
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library_name: transformers
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---
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## MiniCPM-Reranker
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- zh
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- en
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base_model: openbmb/MiniCPM-2B-sft-bf16
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pipeline_tag: text-ranking
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library_name: transformers
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tags:
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- sentence-transformers
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---
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## MiniCPM-Reranker
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