Instructions to use CATIE-AQ/QAmembert-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CATIE-AQ/QAmembert-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="CATIE-AQ/QAmembert-large")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("CATIE-AQ/QAmembert-large") model = AutoModelForQuestionAnswering.from_pretrained("CATIE-AQ/QAmembert-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5f2a5ee11dbddaf85b544679784c6876e4b0974e323b5945dfd0f896abbd188a
- Size of remote file:
- 1.34 GB
- SHA256:
- e96ae23d261076a26f6eb53df4f00bff9ce4711c5f8af86a555df50ab7619c3b
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