Instructions to use hf-internal-testing/tiny-random-layoutlmv3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-layoutlmv3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-layoutlmv3")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-layoutlmv3") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-layoutlmv3") - Notebooks
- Google Colab
- Kaggle
[Awaiting approval] Upload ONNX weights
#1
by Xenova HF Staff - opened
- onnx/model.onnx +3 -0
onnx/model.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:81371c82ad2001f479ccc2adaecf2fe137af950b4140c1fe552f70759d63f186
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size 4160384
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