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:
- e32c203229b463e8ba1331d843b4c406ff604e65052a0e2b4dac1d3ae6ba2d4d
- Size of remote file:
- 365 kB
- SHA256:
- d3852eaaa77bb7d0941b3a04cd31483e9a5d0fb430b1b24cf9a5513f0ead2e0d
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