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:
- 94c6eed4eb1d8c0896c824dd0e51cb34387a23e2d37079c0023d375552d396db
- Size of remote file:
- 6.61 MB
- SHA256:
- 275e31117af0fe11a86878105beb79a2444df7cdcaed09aa1f68b4d3de728674
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