Instructions to use zelcakok/bert-base-squad2-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zelcakok/bert-base-squad2-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="zelcakok/bert-base-squad2-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("zelcakok/bert-base-squad2-uncased") model = AutoModelForQuestionAnswering.from_pretrained("zelcakok/bert-base-squad2-uncased") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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## Latest Result
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```json
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{
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---
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license: mit
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datasets:
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- squad_v2
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language:
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- en
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tags:
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- Bert
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- SQuAD2.0
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- SQuAD
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---
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# Extract QA Model (SQuAD2.0)
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## Model Information
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Pretrained model: google/bert_uncased_L-12_H-768_A-12
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## Training Hyperparameters
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```Python
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epochs = 2
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batch_size = 24
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learning_rate = 3e-5
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max_seq_length = 384
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doc_stride = 128
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max_query_length = 256
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```
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## Latest Result
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```json
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{
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