Deepset/Roberta Base Squad2 Distilled
Distilled RoBERTa model for question-answering tasks
- Status
- Not yet determined
- Last checked
- Unverified
- License
- Open source
- Pricing
- Free tier · from $0
What it is
A distilled version of the RoBERTa model fine-tuned on SQuAD v2.0, optimized for question-answering tasks with reduced computational requirements.
This distilled RoBERTa model offers a balance between performance and resource efficiency, making it ideal for developers who need high accuracy in question-answering tasks without the overhead of larger models.
When it fits — and when it doesn’t
A good fit for
Developers looking for a lightweight yet accurate question-answering model
Projects with limited computational resources but requiring high accuracy in QA tasks
Look elsewhere if
Applications requiring real-time responses where latency is critical
Scenarios needing models that support multiple languages beyond English
Known weaknesses
Each one links to the public issue, changelog or docs page it came from, where we have one.
- 01
Limited support for languages other than English
Model is fine-tuned on SQuAD v2.0, which is an English-language dataset.
- 02
Performance degradation with out-of-domain questions
The model may not perform well when answering questions outside the scope of its training data (SQuAD v2.0).
- 03
Complex setup and configuration for non-expert users
Requires knowledge of Hugging Face's Transformers library and fine-tuning processes.
What it does well
Fine-tuned on SQuAD v2.0 for question-answering tasks
Distilled version of RoBERTa, reducing computational requirements
High accuracy in extracting answers from text
Pricing
- Free tier
- YesOpen source — free to use
- Paid from
- $0
- Model
- Flat rate
- Enterprise plan
- No
Pricing not independently confirmed — check the vendor’s page.
Performance benchmarks
How Fast Is It?
Set up Deepset/Roberta Base Squad2 Distilled
Setup steps, common gotchas and what to check after 30 days.