Instructions to use hf-internal-testing/tiny-random-ElectraModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ElectraModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-ElectraModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-ElectraModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-ElectraModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 66aa43b7138b12e2d7b4d720c7f9044a23b88aa0574ceb217ef8ab2123d1a292
- Size of remote file:
- 1.12 MB
- SHA256:
- 9ccf41a460fd1f477dd76753551e1c561d7c4f9aac1dbca7c7cd47b9287130b0
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