Feature Extraction
Transformers
Safetensors
English
qwen2_vl
image-text-to-text
multimodal-embedding
universal-multimodal-embedding
retrieval
latent-reasoning
mllm
qwen2-vl
Instructions to use Rem520/PLUME-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rem520/PLUME-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Rem520/PLUME-7B")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("Rem520/PLUME-7B") model = AutoModelForImageTextToText.from_pretrained("Rem520/PLUME-7B") - Notebooks
- Google Colab
- Kaggle