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:
- 4bc1e30a23fc1ddc9a948b05bc9de3792ebb59603eda602ec9a9c5a7c0085102
- Size of remote file:
- 16 MB
- SHA256:
- 5edcb5c25e06fc3604790882f6cd60280c188ae52854d7d3547a38bd013521a0
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