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:
- f9631b5628d5424229e21d1d249203ff2f65cf43b18f3c388a2127c589454c91
- Size of remote file:
- 472 kB
- SHA256:
- 8961e0116b64f7aa000cdee56f226922e47168126dfc846a85b935b259311edf
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