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README.md

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@@ -48,21 +48,25 @@ Benchmark for [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1
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### Supported Models
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You can use any BERT model with absolute positions in `text-embeddings-inference`. If the model does not have `safetensors` weights
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you can convert it using [this space](https://huggingface.co/spaces/safetensors/convert).
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You can use any BERT or XLM-RoBERTa model with absolute positions in `text-embeddings-inference`.
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If the model does not have `safetensors` weights you can convert it using [this space](https://huggingface.co/spaces/safetensors/convert).
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**Support for other model types will be added in the future.**
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| MTEB Rank | Model Type | Model ID | Specific Revision |
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|-----------|------------|------------------------|--------------------------------------------------------------------------|
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| 1 | Bert | BAAI/bge-large-en-v1.5 | [refs/pr/5](https://huggingface.co/BAAI/bge-large-en-v1.5/discussions/5) |
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| 2 | | BAAI/bge-base-en-v1.5 | [refs/pr/1](https://huggingface.co/BAAI/bge-base-en-v1.5/discussions/1) |
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| 3 | | llmrails/ember-v1 | |
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| 4 | | thenlper/gte-large | |
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| 5 | | thenlper/gte-base | |
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| 6 | | intfloat/e5-large-v2 | |
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| 7 | | BAAI/bge-small-en-v1.5 | [refs/pr/3](https://huggingface.co/BAAI/bge-small-en-v1.5/discussions/3) |
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| 10 | | intfloat/e5-base-v2 | |
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Examples of supported models:
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| MTEB Rank | Model Type | Model ID | Specific Revision |
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|-----------|--------------|--------------------------------|--------------------------------------------------------------------------|
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| 1 | Bert | BAAI/bge-large-en-v1.5 | [refs/pr/5](https://huggingface.co/BAAI/bge-large-en-v1.5/discussions/5) |
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| 2 | | BAAI/bge-base-en-v1.5 | [refs/pr/1](https://huggingface.co/BAAI/bge-base-en-v1.5/discussions/1) |
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| 3 | | llmrails/ember-v1 | |
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| 4 | | thenlper/gte-large | |
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| 5 | | thenlper/gte-base | |
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| 6 | | intfloat/e5-large-v2 | |
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| 7 | | BAAI/bge-small-en-v1.5 | [refs/pr/3](https://huggingface.co/BAAI/bge-small-en-v1.5/discussions/3) |
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| 10 | | intfloat/e5-base-v2 | |
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| 11 | XLM-RoBERTa | intfloat/multilingual-e5-large | |
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You can explore the list of best performing text embeddings models [here](https://huggingface.co/spaces/mteb/leaderboard).
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