Instructions to use albertoramez/output_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use albertoramez/output_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="albertoramez/output_model")# Load model directly from transformers import AutoProcessor, AutoModelForDocumentQuestionAnswering processor = AutoProcessor.from_pretrained("albertoramez/output_model") model = AutoModelForDocumentQuestionAnswering.from_pretrained("albertoramez/output_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e4a0228edb1f1988bc2762fee0b1939ae2a0153a07083b9d15d997784d5da3d4
- Size of remote file:
- 802 MB
- SHA256:
- 35142ae5f6eda8fe7fc760b993beb91a140b057db2f5f6c599436b13121f969d
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