Instructions to use am-infoweb/layout-test_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use am-infoweb/layout-test_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="am-infoweb/layout-test_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForDocumentQuestionAnswering processor = AutoProcessor.from_pretrained("am-infoweb/layout-test_model") model = AutoModelForDocumentQuestionAnswering.from_pretrained("am-infoweb/layout-test_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from am-infoweb/layout-test_model: direct link, hf CLI and curl.
- Browser
- Download file 802 MB
-
https://huggingface.co/am-infoweb/layout-test_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://am-infoweb/layout-test_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/am-infoweb/layout-test_model/resolve/main/pytorch_model.bin
802 MB
- Xet hash:
- f45471cffb350fc4424f03404e7bcc72cbf1dc5cec9d4c8229ac3bd50e542589
- Size of remote file:
- 802 MB
- SHA256:
- 2e3ec13b72b44357f40612db5622e1b46e8b87975655ce5ac76e440b0b22f2ad
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