Instructions to use microsoft/git-large-textvqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/git-large-textvqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="microsoft/git-large-textvqa")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("microsoft/git-large-textvqa") model = AutoModelForMultimodalLM.from_pretrained("microsoft/git-large-textvqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from microsoft/git-large-textvqa: direct link, hf CLI and curl.
- Browser
- Download file 711 kB
-
https://huggingface.co/microsoft/git-large-textvqa/resolve/main/tokenizer.json
- Command line
-
hf download hf://microsoft/git-large-textvqa/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/microsoft/git-large-textvqa/resolve/main/tokenizer.json
711 kB
File too large to display, you can check the raw version instead.