Instructions to use vumichien/albert-base-v2-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vumichien/albert-base-v2-squad2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="vumichien/albert-base-v2-squad2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("vumichien/albert-base-v2-squad2") model = AutoModelForQuestionAnswering.from_pretrained("vumichien/albert-base-v2-squad2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
tf-albert-base-v2-squad2
This model is a fine-tuned version of twmkn9/albert-base-v2-squad2 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 4.17.0
- TensorFlow 2.8.0
- Tokenizers 0.11.6
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