Instructions to use paru4ik/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use paru4ik/model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="paru4ik/model")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForDocumentQuestionAnswering processor = AutoProcessor.from_pretrained("paru4ik/model") model = AutoModelForDocumentQuestionAnswering.from_pretrained("paru4ik/model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from paru4ik/model: direct link, hf CLI and curl.
- Browser
- Download file 802 MB
-
https://huggingface.co/paru4ik/model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://paru4ik/model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/paru4ik/model/resolve/main/pytorch_model.bin
802 MB
- Xet hash:
- 1058ac1c1f493dbeb30cca269aeed58e8a9d4868b5331e579749d8be53fe6b04
- Size of remote file:
- 802 MB
- SHA256:
- ff562c86610d726eb65db7075c7ebc1866317bf6a36f1e2b807a05aea59003a2
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