Instructions to use hf-internal-testing/tiny-random-squeezebert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-squeezebert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-squeezebert")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-squeezebert") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-squeezebert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2c421f1956d6592be5b493c160565b253da396184e3b7b14a5e52bea32ed3246
- Size of remote file:
- 847 kB
- SHA256:
- 9684d0a832a18823a3da0e477a251f8422136d0faf1c33c00f193cd91622560e
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