Instructions to use teju-1210/transformers-qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use teju-1210/transformers-qa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="teju-1210/transformers-qa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("teju-1210/transformers-qa") model = AutoModelForQuestionAnswering.from_pretrained("teju-1210/transformers-qa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
transformers-qa
This model is a fine-tuned version of distilbert-base-uncased-distilled-squad on an unknown dataset. It achieves the following results on the evaluation set:
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- optimizer: None
- training_precision: float32
Training results
Framework versions
- Transformers 4.41.2
- TensorFlow 2.15.0
- Tokenizers 0.19.1
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