Instructions to use SebastianS/dummy-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SebastianS/dummy-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="SebastianS/dummy-model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("SebastianS/dummy-model") model = AutoModelForMaskedLM.from_pretrained("SebastianS/dummy-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44e6ce2133a85f1d62f020069d9c223089b8c71dc149268c8cb5833ce9b3bbde
- Size of remote file:
- 443 MB
- SHA256:
- 23e3c7b2ac552b676f86d627ac840b9138181091c281d047caa0fa638c5e562a
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