Visual Question Answering
Transformers
Safetensors
PyTorch
English
tinyllava
text-generation
vision-language
custom_code
Eval Results (legacy)
Instructions to use keeeeenw/MicroLlava with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use keeeeenw/MicroLlava with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="keeeeenw/MicroLlava", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("keeeeenw/MicroLlava", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 435 Bytes
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