Instructions to use hf-internal-testing/tiny-random-ElectraForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ElectraForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-ElectraForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-ElectraForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-ElectraForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dac8c1f739bf704114e7138d269954d6f91759d686c6bfe1d5e5fc94e6fbeb17
- Size of remote file:
- 1.04 MB
- SHA256:
- 0e9d04a98ef728e5b1a7138eae6d5f1832f17140f9a066d62aefca0957b677e0
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