Instructions to use lilouuch/QA_bert5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lilouuch/QA_bert5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lilouuch/QA_bert5")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lilouuch/QA_bert5") model = AutoModelForSequenceClassification.from_pretrained("lilouuch/QA_bert5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4586aeadf3f93cd37dbcf4277d92e842bfefcea6d45783ca062d1703a75d25f0
- Size of remote file:
- 4.86 kB
- SHA256:
- 830479e16bd72ada1034c093c8e08d5987cd853b82b5cb073a3c9c75c8fa41b7
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