Instructions to use hf-tiny-model-private/tiny-random-TransfoXLModel 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-TransfoXLModel 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-TransfoXLModel")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-TransfoXLModel", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c6015189e9da3e5ab3a0ed237d497972d929f587506251b2eef4e6a4795f24fb
- Size of remote file:
- 4.58 MB
- SHA256:
- 6ef546a7b6efd2d734bcb2d4290eb3905963e9d3a148312b1b7c92e5c87899d5
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