Instructions to use OpenFace-CQUPT/Human_LLaVA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenFace-CQUPT/Human_LLaVA with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "visual-question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("visual-question-answering", model="OpenFace-CQUPT/Human_LLaVA")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("OpenFace-CQUPT/Human_LLaVA") model = AutoModelForMultimodalLM.from_pretrained("OpenFace-CQUPT/Human_LLaVA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Request: DOI
#3
by g4ndh1 - opened
I am interested in using this model as a reference for a course project proposal.
Thanks for your interest! We generated the DOI for Human_LLaVA model: https://doi.org/10.57967/hf/3090, and the paper's doi will be coming soon.