Instructions to use LIMICS/QAmembert_finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LIMICS/QAmembert_finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="LIMICS/QAmembert_finetuned")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("LIMICS/QAmembert_finetuned") model = AutoModelForQuestionAnswering.from_pretrained("LIMICS/QAmembert_finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 893fc3b727df26ee8d04593104b94c9fe516af464fcde3bd327caedd49ae5849
- Size of remote file:
- 4.92 kB
- SHA256:
- e8c8356a7ca85095eb1408a10cfd0810a34a0ac5d5cb1aa79fc1d99e2902eed9
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