Instructions to use hf-internal-testing/tiny-albert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-albert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-albert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-albert") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-albert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f8964b1cec64e4524a79158f45cc5069ac0c174b59d537c4eae04add08fa942b
- Size of remote file:
- 730 kB
- SHA256:
- e8c50a0be432afd0e75428e41f98be8937fc3f234d99844b1a46603b91e14c62
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