Instructions to use ddrg/math_structure_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ddrg/math_structure_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ddrg/math_structure_bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ddrg/math_structure_bert") model = AutoModel.from_pretrained("ddrg/math_structure_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download mamutbert-training.png from ddrg/math_structure_bert: direct link, hf CLI and curl.
- Browser
- Download file 133 kB
-
https://huggingface.co/ddrg/math_structure_bert/resolve/main/mamutbert-training.png
- Command line
-
hf download hf://ddrg/math_structure_bert/mamutbert-training.png
-
curl -L -o mamutbert-training.png https://huggingface.co/ddrg/math_structure_bert/resolve/main/mamutbert-training.png
133 kB

- Xet hash:
- f688590fd1d14608650b45a9ebcb40e9b376cd05fc8f16155e22cf8beba4b6f4
- Size of remote file:
- 133 kB
- SHA256:
- 257e63bb7f5b372d7dddf643f9142599ab6d415a1741ee40746877bf72f2813f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.