Instructions to use Prem11100/layoutlmv3-Sample3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Prem11100/layoutlmv3-Sample3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Prem11100/layoutlmv3-Sample3")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("Prem11100/layoutlmv3-Sample3") model = AutoModelForSequenceClassification.from_pretrained("Prem11100/layoutlmv3-Sample3") - 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 sha256:28367360548f4e050cc8dedc65165d07dde0d41133ce3501b4b82f4ce9e3ae63
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size 503716188
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