Instructions to use AlpineHealth/date_family_relevancy_extraction_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlpineHealth/date_family_relevancy_extraction_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="AlpineHealth/date_family_relevancy_extraction_model")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("AlpineHealth/date_family_relevancy_extraction_model") model = AutoModelForQuestionAnswering.from_pretrained("AlpineHealth/date_family_relevancy_extraction_model") - Notebooks
- Google Colab
- Kaggle
Upload RobertaForQuestionAnswering
#2
by agr505 - opened
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- pytorch_model.bin +1 -1
config.json
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{
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"_name_or_path": "AlpineHealth/
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"architectures": [
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"RobertaForQuestionAnswering"
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],
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{
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"_name_or_path": "AlpineHealth/date_family_relevancy_extraction_model",
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"architectures": [
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"RobertaForQuestionAnswering"
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],
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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version https://git-lfs.github.com/spec/v1
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oid sha256:22b4abc44daa45d33f3c3fc3c4858f952b85e0fc427f69d57825c55608a6a70b
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size 1417382701
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