Instructions to use Srini99/TQA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Srini99/TQA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Srini99/TQA")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Srini99/TQA") model = AutoModelForQuestionAnswering.from_pretrained("Srini99/TQA") - Notebooks
- Google Colab
- Kaggle
Upload result_dict.json
Browse files- result_dict.json +12 -0
result_dict.json
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{
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"best_val_loss": 0.13029065646515448,
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"epoch": [
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],
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"train_loss": [
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0.35765234559927267
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],
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"val_loss": [
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0.13029065646515448
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]
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}
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