Qwen
/

Qwen3-Embedding-0.6B

Feature Extraction

sentence-transformers

text-generation

sentence-similarity

text-embeddings-inference

text-generation-inference

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alvarobartt HF Staff commited on 10 days ago

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e36abad

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@@ -210,13 +210,13 @@ print(scores.tolist())
 You can either run / deploy TEI on NVIDIA GPUs as:
 ```bash
-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
 ```
 Or on CPU devices as:
 ```bash
-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
 ```
 And then, generate the embeddings sending a HTTP POST request as:

 You can either run / deploy TEI on NVIDIA GPUs as:
 ```bash
+docker run --gpus all -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 --dtype float16
 ```
 Or on CPU devices as:
 ```bash
+docker run -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
 ```
 And then, generate the embeddings sending a HTTP POST request as: