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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c8910ab6cf9b894075795d72ae0b827c39d1948c3e0df401eb174b1dc07f969f
- Size of remote file:
- 16 MB
- SHA256:
- 2bdba8fa9e0a62ede778c05d710c12c19f9af5c9797e1bd655d62d300024300a
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