Instructions to use hf-tiny-model-private/tiny-random-MobileBertModel 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-MobileBertModel 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-MobileBertModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-MobileBertModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-MobileBertModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 061f0923a8802d5798671fc7224910d6cbd992c6968d97204146c96ab2a28686
- Size of remote file:
- 2.87 MB
- SHA256:
- 7ac6ca8c3329f752a5de0355df625678b9d9f0bd23d6d27243618ac818ecc800
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