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:
- 1b4145b9b2ef5b8d055894aa853ea64d9c5b0d5297c4563cc24d51e376080753
- Size of remote file:
- 1.44 MB
- SHA256:
- 5d8d10f2ae69efc2c3735e8b881335cc59b7d359589c9ae39f793b6302cb7589
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