Instructions to use hf-tiny-model-private/tiny-random-DistilBertModel 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-DistilBertModel 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-DistilBertModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-DistilBertModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-DistilBertModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d88b95a1546050a717637bb6c4d9ff1411410c718ce07ea3bb4c253e202f942e
- Size of remote file:
- 354 kB
- SHA256:
- 9ceebfcde0f51f6907be5acc0d8e4748ebb64546d0f952b24f8f18922bfd7b00
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