Instructions to use AntonioTH/Layout-finetuned-fr-model-50instances20-100epochs-5e-05lr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AntonioTH/Layout-finetuned-fr-model-50instances20-100epochs-5e-05lr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="AntonioTH/Layout-finetuned-fr-model-50instances20-100epochs-5e-05lr")# Load model directly from transformers import AutoProcessor, AutoModelForDocumentQuestionAnswering processor = AutoProcessor.from_pretrained("AntonioTH/Layout-finetuned-fr-model-50instances20-100epochs-5e-05lr") model = AutoModelForDocumentQuestionAnswering.from_pretrained("AntonioTH/Layout-finetuned-fr-model-50instances20-100epochs-5e-05lr") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fb24fbdcb3d20b0b9a042ea3ff48c424ad88c4769bb9b96461722c2a96cec544
- Size of remote file:
- 1.48 GB
- SHA256:
- 81df0e0572b1f95a4ecf169209769fa44b16468e8eee67e850c4d87e4df7f995
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.