Instructions to use CUDAOUTOFMEMORY/PLUME-Qwen2-VL-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CUDAOUTOFMEMORY/PLUME-Qwen2-VL-2B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="CUDAOUTOFMEMORY/PLUME-Qwen2-VL-2B")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("CUDAOUTOFMEMORY/PLUME-Qwen2-VL-2B") model = AutoModelForImageTextToText.from_pretrained("CUDAOUTOFMEMORY/PLUME-Qwen2-VL-2B") - Notebooks
- Google Colab
- Kaggle
Add metadata and improve model card
#1
by nielsr HF Staff - opened
This PR improves the model card for PLUME-Qwen2-VL-2B by adding relevant metadata and a citation.
- Added
pipeline_tag: feature-extractionandlibrary_name: transformersto the YAML metadata. - Included the BibTeX citation for the paper.
- Verified and updated links to the paper and project page.
CUDAOUTOFMEMORY changed pull request status to merged