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:
- 5a26021a76ea1a5c2d354a19158faf325ddbde4f2f3b41ff14195fb7f677ebd5
- Size of remote file:
- 17.8 MB
- SHA256:
- f8104de0e0f9b8ab923ac66b31bee4ae132edf05863545fa4a3b69b4774117ae
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