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:
- dfc8e381aec121df5da55e8ad93d9085cf9e244d69100de58b03bdcb721c3737
- Size of remote file:
- 383 kB
- SHA256:
- 545d8feae7cdaa752dfcecd8d480928b31a0f7a0b494877c9ab5ddf504906703
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