Instructions to use hf-tiny-model-private/tiny-random-ElectraModel 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-ElectraModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-ElectraModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-ElectraModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-ElectraModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b6ee3abf67824578c7b1d6db46c4f3bb1bc54f1b75bfb147aacdb1d56c3b74c5
- Size of remote file:
- 1.03 MB
- SHA256:
- 522b85060dcc59386da5650ec6142d87f55d404fbd8eb8983b0941401a9e119c
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