Instructions to use hf-tiny-model-private/tiny-random-IBertForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-IBertForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-tiny-model-private/tiny-random-IBertForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-IBertForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-tiny-model-private/tiny-random-IBertForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3b56f9da7caf1a238e59ad58555659256ab5e50063ffbf2a13eb61067292474b
- Size of remote file:
- 734 kB
- SHA256:
- ad7f057dc9e50644a5633c0800264f2b139bb4186041c22a55bdc59a5ee38e57
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