Instructions to use hf-tiny-model-private/tiny-random-AlbertModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-AlbertModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-AlbertModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-AlbertModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-AlbertModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3a7aee84cf77e6df1a1eb0d5be8592f5166b47d3a14289651a836742cc18d68c
- Size of remote file:
- 15.9 MB
- SHA256:
- bb42cb5cac007b80acc8b108c77962bf75afc84b88743d6f7e5e1608eaab8ecf
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