Instructions to use CATIE-AQ/QAmembert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CATIE-AQ/QAmembert with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="CATIE-AQ/QAmembert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("CATIE-AQ/QAmembert") model = AutoModelForQuestionAnswering.from_pretrained("CATIE-AQ/QAmembert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from CATIE-AQ/QAmembert: direct link, hf CLI and curl.
- Browser
- Download file 2.42 MB
-
https://huggingface.co/CATIE-AQ/QAmembert/resolve/dd4f267d69ce996ee0e28df39bdc7c0bfa903aed/tokenizer.json
- Command line
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hf download hf://CATIE-AQ/QAmembert@dd4f267d69ce996ee0e28df39bdc7c0bfa903aed/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/CATIE-AQ/QAmembert/resolve/dd4f267d69ce996ee0e28df39bdc7c0bfa903aed/tokenizer.json
2.42 MB
File too large to display, you can check the raw version instead.