Instructions to use uclanlp/visualbert-vqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uclanlp/visualbert-vqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="uclanlp/visualbert-vqa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("uclanlp/visualbert-vqa") model = AutoModelForQuestionAnswering.from_pretrained("uclanlp/visualbert-vqa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dcb935466df9f5e90221604867a8da62da5d0972913920fcec27a275fa0bcc37
- Size of remote file:
- 455 MB
- SHA256:
- 0ae380f5aeec7fbf4e4b7c74bf543e5e7e2d6fbb88c1862d9949880af9f68200
路
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