Instructions to use hf-internal-testing/tiny-random-AlbertModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-AlbertModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-AlbertModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-AlbertModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-AlbertModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5b08bfef8656feb0986583dd14e22b4ad64edd75141886dd0d4ad87f32748dcf
- Size of remote file:
- 15.9 MB
- SHA256:
- 32f6524bdd141e49e5f24c6111b0a7659d8cdf394faa1f0923551bcecc02cc1e
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