Feature Extraction
Transformers
Safetensors
qwen3_vl
image-text-to-text
fp8
multimodal embedding
qwen
embedding
compressed-tensors
Instructions to use PIA-SPACE-LAB/Qwen3-VL-Embedding-2B-FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PIA-SPACE-LAB/Qwen3-VL-Embedding-2B-FP8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="PIA-SPACE-LAB/Qwen3-VL-Embedding-2B-FP8")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("PIA-SPACE-LAB/Qwen3-VL-Embedding-2B-FP8") model = AutoModelForMultimodalLM.from_pretrained("PIA-SPACE-LAB/Qwen3-VL-Embedding-2B-FP8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download vocab.json from PIA-SPACE-LAB/Qwen3-VL-Embedding-2B-FP8: direct link, hf CLI and curl.
- Browser
- Download file 2.78 MB
-
https://huggingface.co/PIA-SPACE-LAB/Qwen3-VL-Embedding-2B-FP8/resolve/main/vocab.json
- Command line
-
hf download hf://PIA-SPACE-LAB/Qwen3-VL-Embedding-2B-FP8/vocab.json
-
curl -L -o vocab.json https://huggingface.co/PIA-SPACE-LAB/Qwen3-VL-Embedding-2B-FP8/resolve/main/vocab.json
2.78 MB
File too large to display, you can check the raw version instead.