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:
- 6a3dfbd7fbf0572f200547f038780b982ff97109b3b43dad79f8a4994a2eaf70
- Size of remote file:
- 586 MB
- SHA256:
- 8d80d16ee130a9f3156cc13609208c69b30de3353622b5cd078885499c5ded88
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