Instructions to use Falconsai/question_answering_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Falconsai/question_answering_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Falconsai/question_answering_v2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Falconsai/question_answering_v2") model = AutoModelForQuestionAnswering.from_pretrained("Falconsai/question_answering_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload DistilBertForQuestionAnswering
Browse files- config.json +1 -1
- model.safetensors +1 -1
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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"_name_or_path": "./model",
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"activation": "gelu",
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"architectures": [
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"DistilBertForQuestionAnswering"
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:57b9ddb75e8d84e1520ab820d5bd8f32177f57a438e284df556c237a979831fb
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size 265470032
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