Instructions to use razent/spbert-mlm-zero with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use razent/spbert-mlm-zero with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="razent/spbert-mlm-zero")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("razent/spbert-mlm-zero", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 35d95c1d2c99abb3a24d68b63de819e4191737ec5b48006fe8d9c38607f69b2d
- Size of remote file:
- 524 MB
- SHA256:
- f25d545780d01fe87290c8f8720f807c761981a99451d8a38b0e5cb2e21e8ec6
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