Instructions to use witiko/mathberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use witiko/mathberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="witiko/mathberta")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("witiko/mathberta") model = AutoModelForMaskedLM.from_pretrained("witiko/mathberta") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd4ab36ec2fb8a671fdd2c985d13488cae719bf8de14096d3605e250065dd7b9
- Size of remote file:
- 586 MB
- SHA256:
- b78483d2305e03394670abca0294a74640af0864762839bb27110db23a104886
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