Instructions to use MindNetML/dummy-model2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MindNetML/dummy-model2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="MindNetML/dummy-model2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("MindNetML/dummy-model2") model = AutoModelForMaskedLM.from_pretrained("MindNetML/dummy-model2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cb2c6e32faca0e72ebcebd6ef6d6eb60198fe368bf5f0e850d1ed8d7490b0e6c
- Size of remote file:
- 433 MB
- SHA256:
- cf3e28aeed7fe51553bbfa2c42a662415cefcb590030f2a246421ef927c4a720
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