Instructions to use 1glabs/layoutlmv3-financial-document-classificationyc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 1glabs/layoutlmv3-financial-document-classificationyc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="1glabs/layoutlmv3-financial-document-classificationyc")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("1glabs/layoutlmv3-financial-document-classificationyc") model = AutoModelForSequenceClassification.from_pretrained("1glabs/layoutlmv3-financial-document-classificationyc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from 1glabs/layoutlmv3-financial-document-classificationyc: direct link, hf CLI and curl.
- Browser
- Download file 504 MB
-
https://huggingface.co/1glabs/layoutlmv3-financial-document-classificationyc/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://1glabs/layoutlmv3-financial-document-classificationyc/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/1glabs/layoutlmv3-financial-document-classificationyc/resolve/main/pytorch_model.bin
504 MB
- Xet hash:
- 64ef901de49a67f0e2d9dfb75082869fdaa2ae2fba673f10e8077460609c82cd
- Size of remote file:
- 504 MB
- SHA256:
- b371f7e847ffe12785ff0742fbf4c245ff6360c909dcd3d17d5d22e677de9d73
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