Instructions to use Haniehedi/dummy-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Haniehedi/dummy-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Haniehedi/dummy-model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Haniehedi/dummy-model") model = AutoModelForMaskedLM.from_pretrained("Haniehedi/dummy-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 63980772e707263c07245cef7035a0b7a338e04e15e6726420c3892d09eba5e4
- Size of remote file:
- 541 MB
- SHA256:
- 02de1d12c90e4cf7702b0d54589cc17b8637ad97a70cd42e9275a069fb6376ff
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