Sentence Similarity
sentence-transformers
Safetensors
Transformers
qwen3_vl
image-text-to-text
multimodal embedding
qwen
embedding
Instructions to use Qwen/Qwen3-VL-Embedding-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Qwen/Qwen3-VL-Embedding-2B with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Qwen/Qwen3-VL-Embedding-2B") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use Qwen/Qwen3-VL-Embedding-2B with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Qwen/Qwen3-VL-Embedding-2B") model = AutoModelForMultimodalLM.from_pretrained("Qwen/Qwen3-VL-Embedding-2B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
making the script compatible with transformers 5.2+
#19
by mfarre - opened
Hello - I am working on the Vision Language Models book from O'Reilly and I would like to use qwen3 vl embedding in our video chapter.
In order to simplify how the readers load your model, it would be great to merge this patch so that the model loads properly with transformers 5.2+
thanks for reviewing and merging as soon as possible, it is highly time sensitive.
hey folks, please merge!!
Hey if you still need this, this should help, I built it for others in the situation I was: https://github.com/philmcginty/qwen3-vl-embedding-server