Fork of https://huggingface.co/thenlper/gte small with ONNX weights to be compatible with Transformers.js. See JavaScript usage. gte small General Text Embeddings (GTE) model. The GTE models are trained by Alibaba DAMO Academy. They are mainly based on the BERT framework and currently offer three different sizes of models, including GTE large, GTE base, and GTE small. The GTE models are trained on a large scale corpus of relevance text pairs, covering a wide range of domains and scenarios. This enables the GTE models to be applied to various downstream tasks of text embeddings, including information retrieval , semantic textual similarity , text reranking , etc. Metrics Performance of GTE models were compared with other popular text embedding models on the MTEB benchmark. For more detailed comparison results, please refer to the MTEB leaderboard. Model Name Model Size (GB) Dimension Sequence Length Average (56) Clustering (11) Pair Classification (3) Reranking (4) Retrieval (15) STS (10) Summarization (1) Classification (12) : : : : : : : : : : : : : : : : : : : : : : : : gte large 0.67 1024 512 63.13 46.84 85.00 59.13 52.22 83.35 31.66 73.33 gte base 0.22 768 512 62.39 46.2 84.57…
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