Instructions to use erwannd/question_answer_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use erwannd/question_answer_model 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="erwannd/question_answer_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("erwannd/question_answer_model") model = AutoModelForQuestionAnswering.from_pretrained("erwannd/question_answer_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 125 Bytes
7d019ff | 1 2 3 4 5 6 7 8 | {
"cls_token": "[CLS]",
"mask_token": "[MASK]",
"pad_token": "[PAD]",
"sep_token": "[SEP]",
"unk_token": "[UNK]"
}
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