Add Text Embeddings Inference (TEI) snippet (#21)
Browse files- Add Text Embeddings Inference (TEI) snippet (0acb790751daef0c1a7c5191122056bd16ef9f09)
Co-authored-by: Alvaro Bartolome <[email protected]>
README.md
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@@ -136,6 +136,45 @@ michaelf34/infinity:0.0.68 \
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v2 --model-id Alibaba-NLP/gte-multilingual-reranker-base --revision "main" --dtype bfloat16 --batch-size 32 --device cuda --engine torch --port 7997
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```
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## Evaluation
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Results of reranking based on multiple text retreival datasets
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v2 --model-id Alibaba-NLP/gte-multilingual-reranker-base --revision "main" --dtype bfloat16 --batch-size 32 --device cuda --engine torch --port 7997
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```
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Usage with [Text Embeddings Inference (TEI)](https://github.com/huggingface/text-embeddings-inference):
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- CPU:
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```bash
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docker run --platform linux/amd64 \
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-p 8080:80 \
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-v $PWD/data:/data \
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--pull always \
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ghcr.io/huggingface/text-embeddings-inference:cpu-1.7 \
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--model-id Alibaba-NLP/gte-multilingual-reranker-base
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```
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- GPU:
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```
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docker run --gpus all \
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-p 8080:80 \
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-v $PWD/data:/data \
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--pull always \
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ghcr.io/huggingface/text-embeddings-inference:1.7 \
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--model-id Alibaba-NLP/gte-multilingual-reranker-base
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```
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Then you can send requests to the deployed API via the `/rerank` route (see the [Text Embeddings Inference OpenAPI Specification](https://huggingface.github.io/text-embeddings-inference/) for more details):
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```bash
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curl https://0.0.0.0:8080/rerank \
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-H "Content-Type: application/json" \
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-d '{
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"query": "中国的首都在哪儿",
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"raw_scores": false,
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"return_text": false,
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"texts": [ "北京" ],
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"truncate": true,
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"truncation_direction": "right"
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}'
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```
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## Evaluation
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Results of reranking based on multiple text retreival datasets
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