Instructions to use mpajas/MathBERT_hr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mpajas/MathBERT_hr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mpajas/MathBERT_hr")# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("mpajas/MathBERT_hr") model = AutoModelForPreTraining.from_pretrained("mpajas/MathBERT_hr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0d2b4bc0cf5869dd6a9cb23d5d0d7905500fce7b893b07bbda5f926cf78e1bb7
- Size of remote file:
- 441 MB
- SHA256:
- a805b90575617d2321b71ab518606e932cecfbb260e911aa9c34fdaf6fcadd11
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.