Instructions to use Matthijs0/Distilled-RoBERTa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Matthijs0/Distilled-RoBERTa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Matthijs0/Distilled-RoBERTa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Matthijs0/Distilled-RoBERTa") model = AutoModelForQuestionAnswering.from_pretrained("Matthijs0/Distilled-RoBERTa") - Notebooks
- Google Colab
- Kaggle
Distilled-RoBERTa
The DistilBERT model is a RoBERTa model, which is trained on the SQuAD 2.0 training set, fine-tuned on the NewsQA dataset.
Hyperparameters
batch_size = 16
n_epochs = 3
max_seq_len = 512
learning_rate = 2e-5
optimizer=AdamW
lr_schedule = LinearWarmup
weight_decay=0.01
embeds_dropout_prob = 0.1
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