Instructions to use Prem11100/layoutlmv3-Sample2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Prem11100/layoutlmv3-Sample2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Prem11100/layoutlmv3-Sample2")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("Prem11100/layoutlmv3-Sample2") model = AutoModelForSequenceClassification.from_pretrained("Prem11100/layoutlmv3-Sample2") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:3077fb8e375281392b0938b6e68b9c804fa0d06dc507ad460e4e2936804e7589
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size 503716188
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