Instructions to use tbs17/MathBERT-custom with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tbs17/MathBERT-custom with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="tbs17/MathBERT-custom")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("tbs17/MathBERT-custom") model = AutoModelForMaskedLM.from_pretrained("tbs17/MathBERT-custom", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Pytorch example encoded_input fix
There is a problem like in t5-large from hugging face" with 'size'. Link to solved issue https://github.com/huggingface/transformers/issues/5480. The returned object is a dict, not a tensor for the model. ['input_ids'] fixes PyTorch example.7f37b8a
-
Update README.md
10b6054 -
Update README.md
3e97117 -
Update README.md
019be46
-
remove customvocab file
d46c1c6 -
add mathvocab files
039f5a3
-
Create config.json
v19bd60dc -
Update README.md
v1.10288bf3 -
Create README.md
add v14ef51e6 -
add mathBERT-custom files
391ed79 -
initial commit
33fafa9