Feature Extraction
Transformers
Safetensors
qwen2_5_vl
image-text-to-text
embedding
multimodal
vision-language
mmeb
mveb
Instructions to use HugC/VisME-Qwen25VL-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HugC/VisME-Qwen25VL-3B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="HugC/VisME-Qwen25VL-3B")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("HugC/VisME-Qwen25VL-3B") model = AutoModelForMultimodalLM.from_pretrained("HugC/VisME-Qwen25VL-3B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
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