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Update README.md

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@@ -207,19 +207,19 @@ print(scores.tolist())
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  ### Text Embeddings Inference (TEI) Usage
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- You can either deploy TEI on CPU as:
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  ```bash
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  docker run -p 8080:80 -v hf_cache:/data --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.7.2 --model-id Qwen/Qwen3-Embedding-0.6B
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  ```
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- Or on NVIDIA GPU devices as:
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  ```bash
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  docker run --gpus all -p 8080:80 -v hf_cache:/data --pull always ghcr.io/huggingface/text-embeddings-inference:1.7.2 --model-id Qwen/Qwen3-Embedding-0.6B --dtype float16
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  ```
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- And then generate embeddings sending a HTTP POST request as:
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  ```bash
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  curl http://localhost:8080/embed \
 
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  ### Text Embeddings Inference (TEI) Usage
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+ You can either run / deploy TEI on NVIDIA GPUs as:
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  ```bash
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  docker run -p 8080:80 -v hf_cache:/data --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.7.2 --model-id Qwen/Qwen3-Embedding-0.6B
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  ```
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+ Or on CPU devices as:
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  ```bash
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  docker run --gpus all -p 8080:80 -v hf_cache:/data --pull always ghcr.io/huggingface/text-embeddings-inference:1.7.2 --model-id Qwen/Qwen3-Embedding-0.6B --dtype float16
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  ```
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+ And then, generate the embeddings sending a HTTP POST request as:
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  ```bash
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  curl http://localhost:8080/embed \