Instructions to use hf-internal-testing/tiny-random-ModernBertModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ModernBertModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-ModernBertModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-ModernBertModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-ModernBertModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1e41cd30a4cc4ef24356582a782027cc2f2a0a460b6deeb6fea2065e358f677c
- Size of remote file:
- 6.68 MB
- SHA256:
- af7f6513c5bc8e843e5b9f7e544df07e9dec0fa3f2b7fee27587b62fe71a5c78
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