Instructions to use tanzuhuggingface/question-answering-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tanzuhuggingface/question-answering-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="tanzuhuggingface/question-answering-finetuned")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("tanzuhuggingface/question-answering-finetuned") model = AutoModelForQuestionAnswering.from_pretrained("tanzuhuggingface/question-answering-finetuned") - Notebooks
- Google Colab
- Kaggle
question-answering-finetuned
This model was trained from scratch 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 4.40.2
- TensorFlow 2.16.1
- Tokenizers 0.19.1
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