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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 25fcabae4ecb3e7690516741ed89144983d2a9b2d977c857be3508562d4de1fc
- Size of remote file:
- 4.66 MB
- SHA256:
- 24d8bb27f824290ff5a8f7dac8f00a86155679df6f79efa0ab301dbd06f97242
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