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:
- 70e8a7c96fe0d8ad650355321876750b6670c0ec78f9a4d057c7610a716f8be1
- Size of remote file:
- 418 MB
- SHA256:
- c8b63cc3e2c27c50939f89b64256e075897b21a61012577d160990b873e83dc3
路
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