Visual Question Answering
Transformers
Safetensors
English
Hindi
paligemma
image-text-to-text
Bilingual
text-generation-inference
Instructions to use BhashaAI/ViLaH with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BhashaAI/ViLaH with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="BhashaAI/ViLaH")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("BhashaAI/ViLaH") model = AutoModelForMultimodalLM.from_pretrained("BhashaAI/ViLaH", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec4189f32d6505c56e6d942e8d68586de02493fb711eee5aa3dce4d79fbc380e
- Size of remote file:
- 4.26 MB
- SHA256:
- 8986bb4f423f07f8c7f70d0dbe3526fb2316056c17bae71b1ea975e77a168fc6
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