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:
- 234bc70119cfbab5bdb1b82995cf40999508b2be428d3a7a8a3a44f58d411386
- Size of remote file:
- 1.06 MB
- SHA256:
- 60d78f61a80eda793c7e0fc787972a5c2e474ef3ed3979ae7102680bf4de5b2d
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