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:
- 9e409ee7ba6e15c12957afa3fb33801d6c77d8e7d4e72d76c25161eccfe53247
- Size of remote file:
- 3.13 MB
- SHA256:
- acc5dd8e20912b94cb58047ba493bf5df8538d3373b0f6ced5a3ea89d2c3a193
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