Instructions to use amitha/mllava-llama2-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amitha/mllava-llama2-en 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="amitha/mllava-llama2-en", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForVisualQuestionAnswering model = AutoModelForVisualQuestionAnswering.from_pretrained("amitha/mllava-llama2-en", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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