Instructions to use dilip025/dummy-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dilip025/dummy-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="dilip025/dummy-model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("dilip025/dummy-model") model = AutoModelForMaskedLM.from_pretrained("dilip025/dummy-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 546be7e12d374cca1712ab8b2e8223d37222ecdf4c388482023e9f2baf22f8d9
- Size of remote file:
- 3.39 GB
- SHA256:
- 1ae0e8d09246d28bf2ba60c9d3724d0fc0e578bb742f03659f9cd715c8a36199
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