Instructions to use uclanlp/visualbert-vqa-pre with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uclanlp/visualbert-vqa-pre with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("uclanlp/visualbert-vqa-pre") model = AutoModelForPreTraining.from_pretrained("uclanlp/visualbert-vqa-pre", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from uclanlp/visualbert-vqa-pre: direct link, hf CLI and curl.
- Browser
- Download file 448 MB
-
https://huggingface.co/uclanlp/visualbert-vqa-pre/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://uclanlp/visualbert-vqa-pre/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/uclanlp/visualbert-vqa-pre/resolve/main/pytorch_model.bin
448 MB
- Xet hash:
- b29642bc9f59ce4c9ebd409fd79c564b07f3e2d9a0ec09d0361a17fa33c4e968
- Size of remote file:
- 448 MB
- SHA256:
- 87ed9553b29ff22057748a2587e4ccf771b99de5cf4d2c572c697cb55a72c1bd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.