Instructions to use hf-tiny-model-private/tiny-random-MCTCTModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-MCTCTModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-MCTCTModel")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-MCTCTModel", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc4f7af54d51b79ea6a10d236fc8f040c1f7ca8746709bd6767352c1657d7421
- Size of remote file:
- 23.2 MB
- SHA256:
- 10fe2e902516dd81638f1877eddd18147e96536f814f838e1eed9c7a696b5912
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