Instructions to use alibaba-damo/mgp-str-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alibaba-damo/mgp-str-base with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" 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("image-to-text", model="alibaba-damo/mgp-str-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("alibaba-damo/mgp-str-base") model = AutoModel.from_pretrained("alibaba-damo/mgp-str-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from alibaba-damo/mgp-str-base: direct link, hf CLI and curl.
- Browser
- Download file 592 MB
-
https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://alibaba-damo/mgp-str-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/pytorch_model.bin
592 MB
- Xet hash:
- b3e332036ef0ac12e97ba20e3fc3e7ae427fe0f3fb61df7ac4a513e2459024d2
- Size of remote file:
- 592 MB
- SHA256:
- 5fd53e97eef15dfaa5dd3a10fd44d4d84ad4927e8def4c2e2cc4f373feef5353
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