Instructions to use CATIE-AQ/QAmembert2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CATIE-AQ/QAmembert2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="CATIE-AQ/QAmembert2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("CATIE-AQ/QAmembert2") model = AutoModelForQuestionAnswering.from_pretrained("CATIE-AQ/QAmembert2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c1c11429f419ab6a610a3b2f8004bde314646f490a062d71983d395d1e2edf42
- Size of remote file:
- 5.24 kB
- SHA256:
- 72062642dc2add8ef751c624d7293cbeb981bbb66fd3e82b8a5a9c7380076c5a
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