Instructions to use amroadel1/ltgbert-qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amroadel1/ltgbert-qa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="amroadel1/ltgbert-qa", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("amroadel1/ltgbert-qa", trust_remote_code=True) model = AutoModelForQuestionAnswering.from_pretrained("amroadel1/ltgbert-qa", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 196a5d849963b4c77c003dd8ef35553fd7c178701babe6406411e1211f35f24f
- Size of remote file:
- 3.44 kB
- SHA256:
- b3d1effc10e68ecdafdae1eed3ee9dfa013a8bfa0e28567b4deb2b09f7517a3a
路
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