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:
- 7967f286dbe5255885676a6b5d2031fd6f671d6aa2d1900b5dbd1f1a27a2a408
- Size of remote file:
- 23.2 MB
- SHA256:
- 1f76fca5a568ffbc9cdfc12a5f7ff17088dec3666be561244e114d9d47ff41ff
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