Instructions to use hf-internal-testing/tiny-random-ModernBertForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ModernBertForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-ModernBertForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-ModernBertForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-ModernBertForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d9188a38517bf1a30e083c293ed2ab3ba45e82adf338fa8a1ee087f71c408eba
- Size of remote file:
- 6.9 MB
- SHA256:
- 5e9fa083a8e9ac9c0f9fd8b9608f6984f273d391267c88549b8694567d997fd8
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