Instructions to use firqaaa/indo-dpr-ctx_encoder-single-squad-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use firqaaa/indo-dpr-ctx_encoder-single-squad-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="firqaaa/indo-dpr-ctx_encoder-single-squad-base")# Load model directly from transformers import AutoTokenizer, DPRContextEncoder tokenizer = AutoTokenizer.from_pretrained("firqaaa/indo-dpr-ctx_encoder-single-squad-base") model = DPRContextEncoder.from_pretrained("firqaaa/indo-dpr-ctx_encoder-single-squad-base") - Notebooks
- Google Colab
- Kaggle
Questions Regarding DPR Fine-Tuning and Dataset Preparation
#2
by Imamwahid - opened
Hello Mas Firqa,
I hope you are doing well. I have been exploring the fine-tuned DPR models and would like to ask a few questions regarding the training process and dataset preparation:
- How was the process of the dataset transformed from the SQuAD 2.0 format into the DPR training format?
- How many training instances were used after the dataset preparation process for fine-tuning the DPR model?
- Was the model fine-tuned using IndoBERT? If so, which IndoBERT paper or pretrained model did you refer to?
- Do the context encoder and question encoder use the same encoder architecture or weights?
Thank you for your time and for sharing your work. I really appreciate it and will look forward to your response.