Instructions to use opticalmaterials/opticalbert_qa_squadv1_cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use opticalmaterials/opticalbert_qa_squadv1_cased 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="opticalmaterials/opticalbert_qa_squadv1_cased")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("opticalmaterials/opticalbert_qa_squadv1_cased") model = AutoModelForQuestionAnswering.from_pretrained("opticalmaterials/opticalbert_qa_squadv1_cased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Upload vocab.txt
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Upload tokenizer_config.json
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Upload tokenizer.json
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Upload special_tokens_map.json
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initial commit
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