Instructions to use hf-internal-testing/tiny-random-BertModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BertModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-BertModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-BertModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-BertModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3d69d6c35a4137ce51a920a035f2fee05f0fcfd41c4182b934fc79e0f95a019d
- Size of remote file:
- 450 kB
- SHA256:
- ebc3af0117e7fcc734a5c8b951d8b711dda1e21baaa3052daeddfbc15401bc77
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