Instructions to use hf-internal-testing/tiny-electra with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-electra with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-electra")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-electra") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-electra") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 57f070bd2db5d1fe45a1f8479547355002939d940fcb3f426b6d58c6efde76d5
- Size of remote file:
- 1.69 MB
- SHA256:
- 1df74dfa8af290e22a4f617696eb01f5aba80b0631544ed480a0d4caaff7d12b
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