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:
- b2934afd012df84851357b21c90e248bbf8c2b132d42f1a142b758d56e7c29f8
- Size of remote file:
- 543 MB
- SHA256:
- 218fbf34952941d7f5ba6e753fd0c5ef173c4162e0132f1cfc7a40720aa1480b
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