Instructions to use razent/spbert-mlm-wso-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use razent/spbert-mlm-wso-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="razent/spbert-mlm-wso-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("razent/spbert-mlm-wso-base") model = AutoModelForMaskedLM.from_pretrained("razent/spbert-mlm-wso-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f15d9bd901fd0892ac3645a5d78b46a4c95f354d8dc3f40da3edb1369da011b3
- Size of remote file:
- 433 MB
- SHA256:
- d05aace65f4a4a2390eb1350ef622ac968aafcaf93c8cd7d62a81159068392d6
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