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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44dbacbbac625d49360187bb605b581c9202d26127c95d68971479d33c1f95db
- Size of remote file:
- 4.1 MB
- SHA256:
- 6339e4e419a27b193fe3a914fbb4cbca579911a27ca02b4d02fdca3de8b8cc9f
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