Instructions to use google/matcha-chartqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/matcha-chartqa 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="google/matcha-chartqa")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("google/matcha-chartqa") model = AutoModelForMultimodalLM.from_pretrained("google/matcha-chartqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from google/matcha-chartqa: direct link, hf CLI and curl.
- Browser
- Download file 1.13 GB
-
https://huggingface.co/google/matcha-chartqa/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://google/matcha-chartqa/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/google/matcha-chartqa/resolve/main/pytorch_model.bin
1.13 GB
- Xet hash:
- ee8ec01b5015199917a78811463ca8d3e455bffd0ba4e63f5fe8cb6cbc0cc885
- Size of remote file:
- 1.13 GB
- SHA256:
- f3581eea737164e2a829f6003d42f83e2aabc06e8e2f4d1318b435849c2e0fd3
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