🤖 feature-extraction

Qwen3-Embedding-0.6B

Qwen/Qwen3-Embedding-0.6B

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sentence-transformers
Library
Model Details
Full Model IDQwen/Qwen3-Embedding-0.6B
Pipeline / Taskfeature-extraction
Librarysentence-transformers
Downloads (all-time)8.1M
Likes1.0K
Last Modified4/20/2026
Author / OrgQwen
PrivateNo � public
⚡ Quick Usage (Python)

Using the 🤗 Transformers library. Install with pip install transformers

from transformers import pipeline

# Load the model
pipe = pipeline("feature-extraction", model="Qwen/Qwen3-Embedding-0.6B")

# Run inference
result = pipe("Your input here")
print(result)
����� Tags
sentence-transformerssafetensorsqwen3text-generationtransformerssentence-similarityfeature-extractiontext-embeddings-inferencearxiv:2506.05176base_model:Qwen/Qwen3-0.6B-Basebase_model:finetune:Qwen/Qwen3-0.6B-Baselicense:apache-2.0endpoints_compatibledeploy:azureregion:us
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🚀 Use This Model

Access model files, inference API, and full documentation on Hugging Face.

Open on Hugging Face →Browse Model Files ↗�� Browse All Models
🤖 Task: feature-extraction

This model is designed for the feature-extraction task. Explore more models for this use case.

All feature-extraction Models →
📊 Popularity
Downloads8.1M
����� Community Likes1.0K
🛠�� Requirements
  • Install: pip install sentence-transformers
  • Python 3.8+ recommended for Transformers.
  • GPU (CUDA) speeds up inference significantly.
  • Use model.half() for fp16 on limited VRAM.
👋 Need help with code?