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")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("tbs17/MathBERT-custom") model = AutoModelForMaskedLM.from_pretrained("tbs17/MathBERT-custom") - Notebooks
- Google Colab
- Kaggle
Pytorch example encoded_input fix
#1
by DimOgu - opened
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.
thank you, DimOgu! Already merged your request:-)
tbs17 changed pull request status to merged