Instructions to use tyavika/Tya-Distilbert-CNN256LSTM128-Pytorch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tyavika/Tya-Distilbert-CNN256LSTM128-Pytorch 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="tyavika/Tya-Distilbert-CNN256LSTM128-Pytorch")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("tyavika/Tya-Distilbert-CNN256LSTM128-Pytorch") model = AutoModelForQuestionAnswering.from_pretrained("tyavika/Tya-Distilbert-CNN256LSTM128-Pytorch", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Training in progress, epoch 1
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tyavika/Tya-Distilbert-CNN256LSTM128-Pytorch
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update model card README.md
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Training in progress, epoch 1
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initial commit
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