Instructions to use nflechas/VQArt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nflechas/VQArt with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "visual-question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("visual-question-answering", model="nflechas/VQArt")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForVisualQuestionAnswering processor = AutoProcessor.from_pretrained("nflechas/VQArt") model = AutoModelForVisualQuestionAnswering.from_pretrained("nflechas/VQArt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from nflechas/VQArt: direct link, hf CLI and curl.
- Browser
- Download file 451 MB
-
https://huggingface.co/nflechas/VQArt/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://nflechas/VQArt/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/nflechas/VQArt/resolve/main/pytorch_model.bin
451 MB
- Xet hash:
- 35dba8da8198d25a5ed8da022a234b7c6ee098ba3aa928b76a141dae690866bf
- Size of remote file:
- 451 MB
- SHA256:
- 89e1b0c668d34f66b162c962f51ef55bbb9c775a84e7ec1299baae67669c7555
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