Feature Extraction
sentence-transformers
Safetensors
Transformers
qwen3
text-generation
sentence-similarity
text-embeddings-inference
Instructions to use Qwen/Qwen3-Embedding-0.6B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Qwen/Qwen3-Embedding-0.6B with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Qwen/Qwen3-Embedding-0.6B") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Transformers
How to use Qwen/Qwen3-Embedding-0.6B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Qwen/Qwen3-Embedding-0.6B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3-Embedding-0.6B") model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-Embedding-0.6B") - Inference
- Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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# Qwen3-Embedding-0.6B
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<p align="center">
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| Model Type | Models | Size | Layers | Sequence Length | Embedding Dimension | MRL Support | Instruct Aware |
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|------------------|----------------------|------|--------|-----------------|---------------------|-------------|----------------|
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| Text Embedding | [Qwen3-Embedding-0.6B](https://
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| Text Embedding | [Qwen3-Embedding-4B](https://
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| Text Embedding | [Qwen3-Embedding-8B](https://
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| Text Reranking | [Qwen3-Reranker-0.6B](https://
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| Text Reranking | [Qwen3-Reranker-4B](https://
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| Text Reranking | [Qwen3-Reranker-8B](https://
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> **Note**:: `MRL Support` indicates whether the embedding model supports custom dimensions for the final embedding. `Instruct Aware` notes whether the embedding or reranking model supports customizing the input instruction according to different tasks.
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month = {May},
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year = {2025}
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}
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```
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---
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license: apache-2.0
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base_model:
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- Qwen/Qwen3-0.6B-Base
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library_name: transformers
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---
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# Qwen3-Embedding-0.6B
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<p align="center">
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| Model Type | Models | Size | Layers | Sequence Length | Embedding Dimension | MRL Support | Instruct Aware |
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|------------------|----------------------|------|--------|-----------------|---------------------|-------------|----------------|
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| Text Embedding | [Qwen3-Embedding-0.6B](https://huggingface.co/Qwen/Qwen3-Embedding-0.6B) | 0.6B | 28 | 32K | 1024 | Yes | Yes |
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| Text Embedding | [Qwen3-Embedding-4B](https://huggingface.co/Qwen/Qwen3-Embedding-4B) | 4B | 36 | 32K | 2560 | Yes | Yes |
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| Text Embedding | [Qwen3-Embedding-8B](https://huggingface.co/Qwen/Qwen3-Embedding-8B) | 8B | 36 | 32K | 4096 | Yes | Yes |
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| Text Reranking | [Qwen3-Reranker-0.6B](https://huggingface.co/Qwen/Qwen3-Reranker-0.6B) | 0.6B | 28 | 32K | - | - | Yes |
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| Text Reranking | [Qwen3-Reranker-4B](https://huggingface.co/Qwen/Qwen3-Reranker-4B) | 4B | 36 | 32K | - | - | Yes |
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| Text Reranking | [Qwen3-Reranker-8B](https://huggingface.co/Qwen/Qwen3-Reranker-8B) | 8B | 36 | 32K | - | - | Yes |
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> **Note**:: `MRL Support` indicates whether the embedding model supports custom dimensions for the final embedding. `Instruct Aware` notes whether the embedding or reranking model supports customizing the input instruction according to different tasks.
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month = {May},
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year = {2025}
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}
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```
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