Instructions to use ptran74/DSPFirst-Finetuning-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ptran74/DSPFirst-Finetuning-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="ptran74/DSPFirst-Finetuning-1")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ptran74/DSPFirst-Finetuning-1") model = AutoModelForQuestionAnswering.from_pretrained("ptran74/DSPFirst-Finetuning-1") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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This model is a fine-tuned version of [ahotrod/electra_large_discriminator_squad2_512](https://huggingface.co/ahotrod/electra_large_discriminator_squad2_512) on a generated Questions and Answers dataset from the DSPFirst textbook based on the SQuAD 2.0 format.
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# Dataset
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A visualization of the dataset can be found here
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DatasetDict({
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train: Dataset({
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This model is a fine-tuned version of [ahotrod/electra_large_discriminator_squad2_512](https://huggingface.co/ahotrod/electra_large_discriminator_squad2_512) on a generated Questions and Answers dataset from the DSPFirst textbook based on the SQuAD 2.0 format.
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# Dataset
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A visualization of the dataset can be found [here](https://github.gatech.edu/pages/VIP-ITS/textbook_SQuAD_explore/explore/textbookv1.0/textbook/)
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```
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DatasetDict({
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train: Dataset({
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