Instructions to use h4d35/dummy-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use h4d35/dummy-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="h4d35/dummy-model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("h4d35/dummy-model") model = AutoModelForMaskedLM.from_pretrained("h4d35/dummy-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc4a3e5f266c84c5a3d3fe7be1e32b326e18b804a19577558e5979fecb42a7d8
- Size of remote file:
- 443 MB
- SHA256:
- 49bcca0a8b0e23a9d13e5cc64b16ad539f5316ec5f50e56d2062960592481075
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