Instructions to use hf-tiny-model-private/tiny-random-ElectraForMaskedLM 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-ElectraForMaskedLM 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-ElectraForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-ElectraForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-tiny-model-private/tiny-random-ElectraForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- de60615b239ac18c5199dbad473b656f488ac79cd8afdc52a3ec3f2b58567836
- Size of remote file:
- 1.04 MB
- SHA256:
- b27cc4b2f146ca4dd54c80845b31d73684284e32d44ed388848991e1f1aea61c
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