ettin reranker 32m v1 This is a Cross Encoder model finetuned from jhu clsp/ettin encoder 32m on the cross encoder/ettin reranker v1 data dataset using the sentence transformers library. It computes scores for pairs of texts, which can be used for text reranking and semantic search. See the release blogpost for details on the training recipe, evaluation results, and speed benchmarks against other public rerankers. The Evaluation section below also has the headline numbers. Model Details Model Description Model Type: Cross Encoder Base model: jhu clsp/ettin encoder 32m Maximum Sequence Length: 7999 tokens Number of Output Labels: 1 label Supported Modality: Text Training Dataset: cross encoder/ettin reranker v1 data Language: en License: apache 2.0 Model Sources Documentation: Sentence Transformers Documentation Documentation: Cross Encoder Documentation Repository: Sentence Transformers on GitHub Hugging Face: Cross Encoders on Hugging Face Full Model Architecture Usage Direct Usage (Sentence Transformers) First install the Sentence Transformers library: Then you can load this model and run inference. Click to see the direct usage in Transformers Click to expand Evaluation MTEB(eng…
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