Instructions to use microsoft/git-base-textvqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/git-base-textvqa 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="microsoft/git-base-textvqa")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("microsoft/git-base-textvqa") model = AutoModelForMultimodalLM.from_pretrained("microsoft/git-base-textvqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from microsoft/git-base-textvqa: direct link, hf CLI and curl.
- Browser
- Download file 709 MB
-
https://huggingface.co/microsoft/git-base-textvqa/resolve/main/model.safetensors
- Command line
-
hf download hf://microsoft/git-base-textvqa/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/microsoft/git-base-textvqa/resolve/main/model.safetensors
709 MB
- Xet hash:
- b177e9a5b3e2d2de1b7f8bd7cba38a44c11e4f6e45407265b620dddf0ea835a4
- Size of remote file:
- 709 MB
- SHA256:
- d483a6bf9d687cdcafbf33638f446e1fd41063c6716cf9d8467942f8c3a1d5bf
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