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| 2 models | intfloatIntfloat: E5-Base-v2Remove × | sentence-transformersall-mpnet-base-v2Remove × |
|---|---|---|
| What’s different | The e5-base-v2 embedding model encodes English sentences and paragraphs into a 768-dimensional dense vector space, producing efficient and high-quality semantic embeddings optimized for tasks such as… | A sentence transformation model that has been trained on a wide range of datasets, including but not limited to S2ORC, WikiAnwers, PAQ, Stack Exchange, and Yahoo! Answers. Our model can be used for various… |
| Date | Nov 22, 2023Listed | Feb 28, 2023Listed |
API prices USD · provider configuration shown below | ||
| Listed rate | $0.005 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗ | $0.005 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗ |
| Provider endpoints | 1 endpoint → | 1 endpoint → |
Specifications | ||
| Context window | 512 | 512 |
| Max output | 460 | 460 |
| Parameters | — | — |
| Open weights | Supported | Supported |