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:
- 7569ef275db716d6e23a20af1f747fdabfc79b7757873d891c56bc527013e181
- Size of remote file:
- 6.82 MB
- SHA256:
- 7f6acc9a7d8901d554f826be627507d913d4d37c2a2dfee10fd3c22c3d415a71
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