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README.md
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- **High Performance**: SoTA Multilingual performance compared to ~300M parameter models, competitive with models 2x in size
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- **Multilinguality**: Supports ~100 languages and trained over 1.6B pairs
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- **Flexible Embedding Dimension**: Trained with [Matryoshka Embeddings](https://arxiv.org/abs/2205.13147) with 3x reductions in storage cost with minimal performance degredations
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- **Fully-
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| Model | Params (M) | Emb Dim | BEIR | MIRACL | Pretrain Data | Finetune Data | Code |
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The model can be used through SentenceTransformers and Transformers.
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**Important**: the text prompt *must* include a *task instruction prefix*, instructing the model which task is being performed.
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For queries/questions, please use `search_query: ` and `search_document: ` for the corresponding document
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- **High Performance**: SoTA Multilingual performance compared to ~300M parameter models, competitive with models 2x in size
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- **Multilinguality**: Supports ~100 languages and trained over 1.6B pairs
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- **Flexible Embedding Dimension**: Trained with [Matryoshka Embeddings](https://arxiv.org/abs/2205.13147) with 3x reductions in storage cost with minimal performance degredations
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- **Fully Open-Source**: Model weights, [code](https://github.com/nomic-ai/contrastors), and training data (see code repo) released
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| Model | Params (M) | Emb Dim | BEIR | MIRACL | Pretrain Data | Finetune Data | Code |
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The model can be used through SentenceTransformers and Transformers.
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For best performance on GPU, please install
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```bash
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pip install torch transformers einops git+https://github.com/nomic-ai/megablocks.git
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```
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**Important**: the text prompt *must* include a *task instruction prefix*, instructing the model which task is being performed.
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For queries/questions, please use `search_query: ` and `search_document: ` for the corresponding document
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