Instructions to use Mediocre-Judge/multilingual_bert_AGRO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mediocre-Judge/multilingual_bert_AGRO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Mediocre-Judge/multilingual_bert_AGRO")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Mediocre-Judge/multilingual_bert_AGRO") model = AutoModelForQuestionAnswering.from_pretrained("Mediocre-Judge/multilingual_bert_AGRO", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78c936fa19b55c998df611d6479a6c264573098a3ce679917af20bb162b7d666
- Size of remote file:
- 5.24 kB
- SHA256:
- 88b9bc537cf84bec040f96b2346f4180aa6428217999051f8fc8284b8317adc9
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.