Feature Extraction
Transformers
Safetensors
qwen3_vl
image-text-to-text
multimodal embedding
qwen
embedding
fp8
compressed-tensors
Instructions to use Hyper-AI/Qwen3-VL-Embedding-8B-fp8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hyper-AI/Qwen3-VL-Embedding-8B-fp8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Hyper-AI/Qwen3-VL-Embedding-8B-fp8")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Hyper-AI/Qwen3-VL-Embedding-8B-fp8") model = AutoModelForMultimodalLM.from_pretrained("Hyper-AI/Qwen3-VL-Embedding-8B-fp8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Hyper-AI/Qwen3-VL-Embedding-8B-fp8: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/Hyper-AI/Qwen3-VL-Embedding-8B-fp8/resolve/main/tokenizer.json
- Command line
-
hf download hf://Hyper-AI/Qwen3-VL-Embedding-8B-fp8/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Hyper-AI/Qwen3-VL-Embedding-8B-fp8/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- e1c5ae75d50677cf0cce3ad0441fbf25396122838224b9473c03004e92077538
- Size of remote file:
- 11.4 MB
- SHA256:
- def76fb086971c7867b829c23a26261e38d9d74e02139253b38aeb9df8b4b50a
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