Instructions to use mrm8488/t5-base-finetuned-math-seq-next-term with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/t5-base-finetuned-math-seq-next-term with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mrm8488/t5-base-finetuned-math-seq-next-term") model = AutoModelForSeq2SeqLM.from_pretrained("mrm8488/t5-base-finetuned-math-seq-next-term") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d7716349d74cd52f2f963c133c36e7c4eae4c93738f162dc8e3abb47decb76f2
- Size of remote file:
- 40.6 MB
- SHA256:
- f6e79c5c9736826d8f66672ced3c03bd2ccb5b79dd9ed89ee08028b9b2afa5bf
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.