Instructions to use mlpc-lab/BLIVA_Vicuna with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mlpc-lab/BLIVA_Vicuna 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="mlpc-lab/BLIVA_Vicuna")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mlpc-lab/BLIVA_Vicuna", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update model card for ESTR-CoT
#2 opened over 1 year ago
by
nielsr
Missing config.json
1
#1 opened about 3 years ago
by
arnaudstiegler