Instructions to use Falconsai/question_answering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Falconsai/question_answering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Falconsai/question_answering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Falconsai/question_answering") model = AutoModelForQuestionAnswering.from_pretrained("Falconsai/question_answering") - Notebooks
- Google Colab
- Kaggle
Upload DistilBertForQuestionAnswering
Browse files- config.json +1 -1
- pytorch_model.bin +2 -2
config.json
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"_name_or_path": "
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"activation": "gelu",
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"architectures": [
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"DistilBertForQuestionAnswering"
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{
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"_name_or_path": "./model",
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"activation": "gelu",
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"architectures": [
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"DistilBertForQuestionAnswering"
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pytorch_model.bin
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size 265491109
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