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:
- 511bbfb0a35d626b65f27c4a5c1a743bb63315a0a9bb82147decc46cdcddfc84
- Size of remote file:
- 1.03 MB
- SHA256:
- 35e951caf8bf9e944838c20224aeba9e87d7dbc6805b74f3e77f5ce6bf6ff750
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