Instructions to use hf-internal-testing/tiny-random-IBertModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-IBertModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-IBertModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-IBertModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-IBertModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c5bbdf7928b69c28246dbddba06136262357f4e11b26151a3366f951f4c649e0
- Size of remote file:
- 815 kB
- SHA256:
- ae56446d88f39685acb1e974941f2286de550c46f6b674f757aed97f7e73829a
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