Instructions to use Prem11100/layoutlmv3-financial-document-classification_7_classes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Prem11100/layoutlmv3-financial-document-classification_7_classes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Prem11100/layoutlmv3-financial-document-classification_7_classes")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("Prem11100/layoutlmv3-financial-document-classification_7_classes") model = AutoModelForSequenceClassification.from_pretrained("Prem11100/layoutlmv3-financial-document-classification_7_classes", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Prem11100/layoutlmv3-financial-document-classification_7_classes: direct link, hf CLI and curl.
- Browser
- Download file 504 MB
-
https://huggingface.co/Prem11100/layoutlmv3-financial-document-classification_7_classes/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Prem11100/layoutlmv3-financial-document-classification_7_classes/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Prem11100/layoutlmv3-financial-document-classification_7_classes/resolve/main/pytorch_model.bin
504 MB
- Xet hash:
- ea37da2f5b96c4f0450e1e3d0a3d315ec6b989adfb24b79ae79413c4b0b673d8
- Size of remote file:
- 504 MB
- SHA256:
- 6d8777c7a5ff9c64c90d794a626bd22f03d7186b8d699730e90d2bcbe2f19c40
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