Instructions to use arbitropy/mt5-base-bcoqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arbitropy/mt5-base-bcoqa with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("arbitropy/mt5-base-bcoqa") model = AutoModelForSeq2SeqLM.from_pretrained("arbitropy/mt5-base-bcoqa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7bdc6af837ac5cd097b137ed99d7c9cbe1e8029ec92a0d0bc6d1127a7ad76d8a
- Size of remote file:
- 16.3 MB
- SHA256:
- 20ce747f56c3a3abbd1d60f2ce1c6c51decbfbc7ca49247aca30eed62c32d900
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.