Instructions to use minsik-oh/dummy-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use minsik-oh/dummy-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="minsik-oh/dummy-model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("minsik-oh/dummy-model") model = AutoModelForMaskedLM.from_pretrained("minsik-oh/dummy-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6a63c753877e5473763f1024cf401ff81f005259f51aab855cb18b63f5982bc1
- Size of remote file:
- 443 MB
- SHA256:
- 44c0e284056e40c691db9f54c0502df836365769cb2d64c7d60d0e50a21a9b45
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